Completing Statements MCQs for Sub-Topics of Topic 16: Statistics & Probability

Question 1. The collection of numerical figures and facts, collected for a definite purpose, is known as____

(A) Information

(B) Results

(C) Data

(D) Analysis

Question 2. Data that has been gathered from a source but has not been processed or organized in any way is referred to as____

(A) Secondary data

(B) Summarized data

(C) Raw data

(D) Interpreted data

Question 3. A single measurement or record of a variable, such as a student's height or mark, is called an____

(A) Experiment

(B) Variable

(C) Observation

(D) Dataset

Question 4. A characteristic that can take on different values for different individuals or objects, like age or income, is termed a____

(A) Constant

(B) Variable

(C) Attribute

(D) Observation

Question 5. The number of defective items found in a sample of products is an example of a __________ variable.

(A) Continuous

(B) Qualitative

(C) Discrete

(D) Categorical

Question 6. The process of gathering data from different sources is known as data____

(A) Analysis

(B) Presentation

(C) Collection

(D) Interpretation

Question 7. Data published in a government census report is considered __________ data for a researcher using it for their study.

(A) Primary

(B) Raw

(C) Experimental

(D) Secondary

Question 8. Arranging data into a systematic order, such as an array or a frequency table, falls under the stage of data____

(A) Collection

(B) Organization

(C) Presentation

(D) Interpretation

Question 9. Summarizing data using tables, charts, and graphs is part of the data __________ stage.

(A) Organization

(B) Analysis

(C) Presentation

(D) Interpretation

Question 10. Drawing conclusions and making inferences based on the patterns and summaries found in data is the final stage of data handling, known as data____

(A) Collection

(B) Analysis

(C) Presentation

(D) Interpretation

Question 1. The number of times a particular observation occurs in a given set of data is called its____

(A) Range

(B) Class mark

(C) Frequency

(D) Cumulative frequency

Question 2. A table that shows the frequency of each distinct value or class interval in a dataset is called a____

(A) Correlation table

(B) Summary table

(C) Frequency distribution table

(D) Raw data table

Question 3. In the class interval 50-60, 50 is the __________ and 60 is the __________. (assuming exclusive classes)

(A) Upper limit, Lower limit

(B) Lower limit, Upper limit

(C) Class mark, Frequency

(D) Frequency, Class mark

Question 4. The difference between the upper class limit and the lower class limit of a class interval is known as the class____

(A) Mark

(B) Boundary

(C) Frequency

(D) Size or Width

Question 5. The midpoint of a class interval, calculated as (Lower limit + Upper limit) / 2, is called the class____

(A) Boundary

(B) Size

(C) Mark

(D) Frequency

Question 6. In an inclusive class interval like 20-29, an observation with a value of 29 is included in the class____

(A) 10-19

(B) 20-29

(C) 30-39

(D) Neither

Question 7. The sum of frequencies of all observations up to the upper limit of a particular class interval is called its __________ frequency.

(A) Simple

(B) Relative

(C) Cumulative

(D) Class

Question 8. A frequency distribution table is called 'ungrouped' when it shows the frequency for each individual____

(A) Class interval

(B) Cumulative frequency

(C) Distinct value or observation

(D) Class mark

Question 9. When constructing a grouped frequency distribution table, the class intervals should typically be mutually exclusive and __________ to cover the entire range of data.

(A) Non-overlapping, exhaustive

(B) Inclusive, non-inclusive

(C) Random, biased

(D) Disjoint, partial

Question 10. If the 'less than' cumulative frequency for the class 40-50 is 28, and for the class 50-60 is 45, the frequency of the class 50-60 is____

(A) 28

(B) 45

(C) $45 - 28 = 17$

(D) $45 + 28 = 73$

Question 1. A graphical representation that uses symbols or pictures to represent data is called a____

(A) Bar graph

(B) Histogram

(C) Pictograph

(D) Pie chart

Question 2. A graph consisting of bars of uniform width with equal space between them, used for categorical or discrete data, is called a____

(A) Histogram

(B) Frequency polygon

(C) Bar graph

(D) Ogive

Question 3. A graph that represents data as sectors of a circle, where the area of each sector is proportional to the part of the whole it represents, is called a____

(A) Bar graph

(B) Line graph

(C) Scatter plot

(D) Pie chart

Question 4. To compare two sets of related data simultaneously, such as sales figures for two different years across several product categories, the most suitable basic chart is a____

(A) Single bar graph

(B) Double bar graph

(C) Pie chart

(D) Pictograph

Question 5. If a sector in a pie chart represents 40% of the total, the angle of that sector at the center is____

(A) $40^\circ$

(B) $90^\circ$

(C) $(40/100) \times 360^\circ = 144^\circ$

(D) $180^\circ$

Question 6. In a bar graph, the height or length of each bar is proportional to the __________ or value it represents.

(A) Class limit

(B) Class size

(C) Frequency

(D) Cumulative frequency

Question 7. The total angle at the center of a pie chart is always____

(A) $100^\circ$

(B) $180^\circ$

(C) $360^\circ$

(D) Equal to the sum of the data values

Question 8. Which type of basic chart is best suited for showing the distribution of different types of vehicles (car, bike, bus) in a parking lot?

(A) Histogram

(B) Frequency polygon

(C) Bar graph

(D) Ogive

Question 9. If a pictograph uses a symbol representing 50 items, and you need to represent 225 items, you would use __________ symbols.

(A) 4 full

(B) 5 full

(C) 4 full and a half

(D) $225/50 = 4.5$, so 4 full and a half

Question 10. Basic charts are primarily used for data __________ to provide a clear visual summary.

(A) Collection

(B) Organization

(C) Analysis

(D) Presentation

Question 1. A graphical representation of a frequency distribution of grouped continuous data, where bars are adjacent, is called a____

(A) Bar graph

(B) Frequency polygon

(C) Histogram

(D) Pie chart

Question 2. In a histogram with equal class widths, the height of each bar represents the __________ of the corresponding class.

(A) Class mark

(B) Class size

(C) Frequency

(D) Cumulative frequency

Question 3. A frequency polygon is formed by joining the midpoints of the tops of adjacent bars in a____

(A) Bar graph

(B) Histogram

(C) Pie chart

(D) Ogive

Question 4. When drawing a frequency polygon directly from a frequency table, the points plotted are the class marks on the x-axis and the corresponding __________ on the y-axis.

(A) Class limits

(B) Class boundaries

(C) Frequencies

(D) Cumulative frequencies

Question 5. If a histogram has unequal class widths, the area of each bar should be proportional to the class____, which is achieved by plotting frequency density on the y-axis.

(A) Mark

(B) Size

(C) Frequency

(D) Boundary

Question 6. To make the area under the frequency polygon equal to the area under the corresponding histogram, the polygon is closed by connecting the midpoints of the extreme classes to the x-axis at the boundaries of hypothetical classes with zero __________.

(A) Class marks

(B) Frequencies

(C) Class sizes

(D) Cumulative frequencies

Question 7. A histogram is primarily used to visualize the distribution of __________ data.

(A) Categorical

(B) Discrete (ungrouped)

(C) Continuous (grouped)

(D) Ordinal

Question 8. Comparing the shapes of two frequency distributions can be effectively done by drawing their __________ on the same axes.

(A) Histograms

(B) Frequency polygons

(C) Ogives

(D) Bar graphs

Question 9. In a histogram, the x-axis represents the class intervals or __________, showing the range of values.

(A) Frequencies

(B) Class marks

(C) Class boundaries

(D) Cumulative frequencies

Question 10. Converting inclusive class intervals to exclusive class boundaries is necessary before drawing a histogram to ensure the continuity between____

(A) Frequencies

(B) Class marks

(C) Bars

(D) Cumulative frequencies

Question 1. A graphical representation of a cumulative frequency distribution is commonly known as an____

(A) Histogram

(B) Frequency polygon

(C) Ogive

(D) Bar chart

Question 2. To construct a 'less than' ogive, cumulative frequencies are plotted against the __________ of the class intervals.

(A) Lower limits

(B) Upper limits or upper boundaries

(C) Class marks

(D) Frequencies

Question 3. To construct a 'more than' ogive, cumulative frequencies are plotted against the __________ of the class intervals.

(A) Upper limits or upper boundaries

(B) Lower limits or lower boundaries

(C) Class marks

(D) Frequencies

Question 4. The Median of a distribution can be estimated graphically by finding the value on the x-axis corresponding to $N/2$ on the y-axis of a____

(A) Histogram

(B) Frequency polygon

(C) Ogive ('less than' or 'more than')

(D) Bar chart

Question 5. The intersection point of the 'less than' ogive and the 'more than' ogive gives the estimated __________ on the x-axis.

(A) Mean

(B) Median

(C) Mode

(D) Quartiles

Question 6. A 'less than' ogive is typically a curve that is always____

(A) Decreasing

(B) Increasing

(C) Bell-shaped

(D) Symmetric

Question 7. Ogives are particularly useful for estimating __________ values like Median, Quartiles, and Percentiles.

(A) Mean

(B) Mode

(C) Positional

(D) Absolute

Question 8. To find the number of observations below a certain value from an ogive, you would use the __________ ogive and locate the value on the x-axis to find the corresponding cumulative frequency on the y-axis.

(A) More than

(B) Less than

(C) Frequency polygon

(D) Histogram

Question 9. The y-coordinate of the intersection point of the two ogives is equal to____

(A) The Median value

(B) The total frequency (N)

(C) Half of the total frequency ($N/2$)

(D) The frequency of the median class

Question 10. When plotting a 'less than' ogive, the curve usually starts from a cumulative frequency of 0 at the lower boundary of the __________ class.

(A) Median

(B) Modal

(C) Last

(D) First

Question 1. A single value that represents the center or typical value of a dataset is called a measure of central____

(A) Dispersion

(B) Skewness

(C) Tendency

(D) Variability

Question 2. The sum of all observations in a dataset divided by the number of observations is the____

(A) Median

(B) Mode

(C) Arithmetic Mean

(D) Range

Question 3. For grouped data, the calculation of the Mean using the Direct Method involves summing the product of each class's frequency and its____

(A) Lower limit

(B) Upper limit

(C) Class mark

(D) Cumulative frequency

Question 4. If a constant value is added to every observation in a dataset, the arithmetic mean of the new dataset will be equal to the original mean plus____

(A) The square of the constant

(B) The constant itself

(C) Zero

(D) The constant multiplied by the number of observations

Question 5. If every observation in a dataset is multiplied by a constant 'k', the arithmetic mean of the new dataset will be equal to the original mean multiplied by____

(A) The square of k

(B) k

(C) k plus the original mean

(D) The original mean divided by k

Question 6. The sum of the deviations of individual observations from their arithmetic mean is always equal to____

(A) The number of observations

(B) The mean itself

(C) Zero

(D) The standard deviation

Question 7. The Mean is significantly affected by __________ values, unlike the Median or Mode.

(A) Middle

(B) Frequent

(C) Extreme (outliers)

(D) Central

Question 8. For grouped data, methods like the Assumed Mean Method and Step-Deviation Method are essentially shortcuts to calculate the arithmetic mean and yield the same result as the __________ Method.

(A) Median

(B) Mode

(C) Direct

(D) Graphical

Question 9. Measures of central tendency are often referred to as __________ because they aim to represent the typical value of a dataset.

(A) Deviations

(B) Dispersions

(C) Averages

(D) Frequencies

Question 10. The arithmetic mean requires data to be on at least the __________ scale for meaningful calculation.

(A) Nominal

(B) Ordinal

(C) Interval or Ratio

(D) Qualitative

Question 1. When a dataset is arranged in ascending or descending order, the middle value is called the____

(A) Mean

(B) Mode

(C) Median

(D) Mid-range

Question 2. For an ungrouped dataset with an odd number of observations (n), the Median is the value at the __________ position after ordering.

(A) $n/2$

(B) $(n+1)/2$

(C) $n$

(D) 1st

Question 3. For an ungrouped dataset with an even number of observations (n), the Median is the average of the values at the __________ and __________ positions after ordering.

(A) $n/2$, $n/2 + 1$

(B) $(n+1)/2$, $(n+3)/2$

(C) 1st, last

(D) Median class lower limit, upper limit

Question 4. The Median is a positional average because its value depends on its position in the __________ dataset.

(A) Raw

(B) Grouped

(C) Ordered

(D) Random

Question 5. For grouped data, the first step in calculating the Median is to find the cumulative____

(A) Frequency

(B) Class mark

(C) Class size

(D) Mean

Question 6. The class interval containing the $(\frac{N}{2})^{th}$ observation, where N is the total frequency, is called the __________ class.

(A) Modal

(B) Mean

(C) Frequency

(D) Median

Question 7. The Median is a more robust measure of central tendency than the Mean when the dataset contains____

(A) Symmetric values

(B) Small values

(C) Extreme values or outliers

(D) Consistent values

Question 8. The Median can be estimated graphically from the intersection point of the 'less than' and 'more than'____

(A) Histograms

(B) Frequency polygons

(C) Bar graphs

(D) Ogives

Question 9. In the Median formula for grouped data, 'L' represents the lower __________ of the median class.

(A) Limit

(B) Boundary

(C) Mark

(D) Frequency

Question 10. The Median is a suitable measure of central tendency for data that is numerical or can be ranked, such as data measured on the __________ scale.

(A) Nominal

(B) Ordinal

(C) Qualitative

(D) Categorical

Question 1. The value that appears most often in a dataset is called the____

(A) Mean

(B) Median

(C) Mode

(D) Midpoint

Question 2. A dataset can have one mode (unimodal), two modes (bimodal), or more than two modes (multimodal), or even____

(A) No mode

(B) Infinite modes

(C) Zero as the mode

(D) Negative mode

Question 3. For grouped data, the class interval with the highest frequency is identified as the __________ class.

(A) Median

(B) Mean

(C) Modal

(D) Cumulative

Question 4. The Mode is the most appropriate measure of central tendency for __________ data, such as favourite colours or types of vehicles.

(A) Numerical

(B) Continuous

(C) Qualitative (Nominal)

(D) Ordinal

Question 5. For a symmetric distribution, the Mean, Median, and Mode are all____

(A) Different

(B) Equal

(C) Ordered in ascending value

(D) Ordered in descending value

Question 6. For a positively skewed distribution, the order of Mean, Median, and Mode from lowest to highest value is typically Mode, Median, __________.

(A) Median

(B) Mode

(C) Mean

(D) Range

Question 7. For a negatively skewed distribution, the order of Mean, Median, and Mode from lowest to highest value is typically __________, Median, Mode.

(A) Mode

(B) Median

(C) Mean

(D) Range

Question 8. The empirical formula relating Mean, Median, and Mode for moderately skewed distributions is approximately Mode = 3 Median - 2____

(A) Range

(B) Standard Deviation

(C) Variance

(D) Mean

Question 9. The Mode can be estimated graphically from the peak of the distribution as shown in a____

(A) Bar graph

(B) Pie chart

(C) Histogram

(D) Ogive

Question 10. Unlike the Mean and Median, the Mode is not affected by __________ values.

(A) Frequent

(B) Central

(C) Ordered

(D) Extreme (outliers)

Question 1. Measures of dispersion describe the __________ or variability of a dataset.

(A) Center

(B) Shape

(C) Spread

(D) Frequency

Question 2. The difference between the highest and the lowest value in a dataset is called the____

(A) Mean deviation

(B) Interquartile range

(C) Range

(D) Standard deviation

Question 3. The Range is a simple measure of dispersion, but its main limitation is that it only considers the two __________ values.

(A) Middle

(B) Most frequent

(C) Extreme (maximum and minimum)

(D) Central

Question 4. The average of the absolute deviations of individual observations from a measure of central tendency (like Mean or Median) is called the Mean____

(A) Range

(B) Dispersion

(C) Deviation

(D) Spread

Question 5. In calculating Mean Deviation, absolute values $|x_i - A|$ are used to ensure that positive and negative deviations do not __________ each other out.

(A) Amplify

(B) Cancel

(C) Multiply

(D) Average

Question 6. If a constant 'c' is added to every observation in a dataset, the Range of the new dataset will be equal to the original Range____

(A) Plus c

(B) Minus c

(C) Multiplied by c

(D) Remains unchanged

Question 7. If every observation in a dataset is multiplied by a positive constant 'k', the Mean Deviation of the new dataset will be equal to the original Mean Deviation multiplied by____

(A) k

(B) $k^2$

(C) $|k|$

(D) Remains unchanged

Question 8. Mean Deviation from the Median is minimum compared to Mean Deviation calculated from any other __________ value.

(A) Extreme

(B) Most frequent

(C) Central

(D) Average

Question 9. For grouped data, the Mean Deviation formula uses the sum of frequencies multiplied by the __________ deviations from the chosen average, divided by the total frequency.

(A) Squared

(B) Absolute

(C) Raw

(D) Cumulative

Question 10. Measures of dispersion provide information about the variability of data, which is important for understanding how representative the measure of central tendency____

(A) Is calculated

(B) Is

(C) Is interpreted

(D) Varies

Question 1. The average of the squared deviations of individual observations from their mean is called the____

(A) Mean deviation

(B) Standard deviation

(C) Variance

(D) Coefficient of variation

Question 2. The positive square root of the Variance is called the Standard____

(A) Error

(B) Deviation

(C) Mean

(D) Range

Question 3. If a constant 'c' is added to every observation in a dataset, the Variance of the new dataset will be equal to the original Variance____

(A) Plus c

(B) Minus c

(C) Multiplied by c

(D) Remains unchanged

Question 4. If every observation in a dataset is multiplied by a constant 'k', the Standard Deviation of the new dataset will be equal to the original Standard Deviation multiplied by____

(A) k

(B) $k^2$

(C) $|k|$

(D) Remains unchanged

Question 5. The units of Variance are the __________ of the units of the original data.

(A) Same as

(B) Square of

(C) Square root of

(D) Logarithm of

Question 6. The Standard Deviation is widely used because it is in the same __________ as the original data and the mean, making interpretation easier.

(A) Scale

(B) Range

(C) Units

(D) Magnitude

Question 7. If all data points in a dataset are identical, the Variance and Standard Deviation are both equal to____

(A) The mean

(B) 1

(C) The range

(D) Zero

Question 8. For a sample of size n, the sample variance $s^2$ often uses a denominator of __________ to provide an unbiased estimate of the population variance.

(A) n

(B) $n-1$

(C) $\sqrt{n}$

(D) $n-2$

Question 9. Variance and Standard Deviation are suitable measures of dispersion for data measured on the __________ or __________ scale.

(A) Nominal, Ordinal

(B) Interval, Ratio

(C) Qualitative, Categorical

(D) Discrete, Continuous

Question 10. The Standard Deviation measures the typical distance of observations from the____

(A) Median

(B) Mode

(C) Range

(D) Mean

Question 1. Measures of relative dispersion are used to compare the variability of two or more datasets when they have different units of measurement or significantly different __________.

(A) Ranges

(B) Standard deviations

(C) Means

(D) Frequencies

Question 2. The most common measure of relative dispersion is the Coefficient of __________, calculated as (Standard Deviation / Mean) $\times$ 100.

(A) Range

(B) Quartile Deviation

(C) Variance

(D) Variation

Question 3. The Coefficient of Variation is a dimensionless measure, usually expressed as a __________, making it suitable for comparing variability across different scales.

(A) Ratio

(B) Decimal

(C) Percentage

(D) Fraction

Question 4. A higher Coefficient of Variation indicates __________ variability relative to the mean, suggesting less consistency.

(A) Less

(B) Equal

(C) More

(D) Zero

Question 5. The Coefficient of Variation is meaningful only when the Mean of the distribution is non-zero, as division by zero is __________.

(A) Positive

(B) Negative

(C) Defined

(D) Undefined

Question 6. Comparing the batting consistency of two cricket players with different average scores is best done using the Coefficient of __________.

(A) Range

(B) Quartile Deviation

(C) Variation

(D) Mean Deviation

Question 7. Moments are mathematical concepts used to describe the characteristics of a distribution based on the average of powers of deviations from a point. Moments calculated about the origin are called __________ moments.

(A) Central

(B) Standardized

(C) Raw

(D) Absolute

Question 8. Moments calculated about the Mean are called __________ moments.

(A) Raw

(B) Central

(C) Standardized

(D) Absolute

Question 9. The first raw moment about the origin is equal to the __________ of the distribution.

(A) Variance

(B) Standard Deviation

(C) Mean

(D) Median

Question 10. The second central moment (moment about the mean) is equal to the __________ of the distribution.

(A) Mean

(B) Variance

(C) Skewness

(D) Kurtosis

Question 1. Skewness is a measure of the __________ of a probability distribution.

(A) Central tendency

(B) Dispersion

(C) Asymmetry

(D) Peakedness

Question 2. A distribution with a longer tail to the right is said to be __________ skewed.

(A) Negatively

(B) Positively

(C) Symmetric

(D) Meso

Question 3. A distribution with a longer tail to the left is said to be __________ skewed.

(A) Negatively

(B) Positively

(C) Symmetric

(D) Lepto

Question 4. For a symmetric distribution, the coefficient of skewness is equal to____

(A) 1

(B) -1

(C) 0

(D) The mean

Question 5. Kurtosis is a measure of the __________ and tail heaviness of a distribution.

(A) Asymmetry

(B) Dispersion

(C) Peakedness

(D) Center

Question 6. A distribution that is more peaked and has fatter tails than the normal distribution is called____

(A) Platykurtic

(B) Mesokurtic

(C) Leptokurtic

(D) Symmetric

Question 7. The normal distribution is considered to be __________ in terms of kurtosis.

(A) Platykurtic

(B) Mesokurtic

(C) Leptokurtic

(D) Skewed

Question 8. A distribution that is flatter and has thinner tails than the normal distribution is called____

(A) Platykurtic

(B) Mesokurtic

(C) Leptokurtic

(D) Uniform

Question 9. For a positively skewed distribution, the Mean is typically __________ than the Median.

(A) Less than

(B) Equal to

(C) Greater than

(D) Unrelated to

Question 10. Bowley's coefficient of skewness is based on the position of the __________ and Median.

(A) Mean

(B) Mode

(C) Quartiles

(D) Standard Deviation

Question 1. Measures like quartiles and percentiles divide an ordered dataset into a specific number of equal____

(A) Frequencies

(B) Ranges

(C) Parts

(D) Deviations

Question 2. Quartiles divide an ordered dataset into __________ equal parts.

(A) 2

(B) 4

(C) 10

(D) 100

Question 3. The second quartile (Q2) is always equal to the __________ of the dataset.

(A) Mean

(B) Mode

(C) Median

(D) Mean Deviation

Question 4. Percentiles divide an ordered dataset into __________ equal parts.

(A) 4

(B) 10

(C) 50

(D) 100

Question 5. The $k^{th}$ percentile ($P_k$) is the value below which approximately __________ percent of the observations fall.

(A) k

(B) 100-k

(C) k/100

(D) 100/k

Question 6. The Interquartile Range (IQR) is calculated as the difference between the third quartile (Q3) and the __________ quartile (Q1).

(A) Second

(B) First

(C) Fourth

(D) Zero

Question 7. The Quartile Deviation (QD) is also known as the Semi-Interquartile Range and is equal to half of the __________.

(A) Range

(B) Mean Deviation

(C) Standard Deviation

(D) Interquartile Range (IQR)

Question 8. Quartiles and percentiles are measures of __________ that are resistant to extreme values.

(A) Central tendency

(B) Dispersion

(C) Skewness

(D) Kurtosis

Question 9. The percentile rank of a value indicates the percentage of observations in the dataset that are __________ or equal to that value.

(A) Less than

(B) Greater than

(C) Exactly

(D) Not less than

Question 10. For grouped data, quartiles and percentiles can be estimated using formulas similar to the Median formula, using __________ frequencies and class boundaries.

(A) Class

(B) Relative

(C) Cumulative

(D) Simple

Question 1. Correlation measures the strength and direction of the __________ relationship between two variables.

(A) Non-linear

(B) Exponential

(C) Linear

(D) Quadratic

Question 2. A graphical tool used to visualize the relationship between two quantitative variables is called a Scatter____

(A) Plot

(B) Diagram

(C) Chart

(D) Graph

Question 3. If two variables tend to increase together, they have a __________ correlation.

(A) Negative

(B) Zero

(C) Positive

(D) Perfect

Question 4. If one variable tends to increase as the other decreases, they have a __________ correlation.

(A) Negative

(B) Zero

(C) Positive

(D) Strong

Question 5. Karl Pearson's Coefficient of Correlation (r) measures the strength and direction of the linear relationship and ranges from -1 to____

(A) 0

(B) 1

(C) 100

(D) Infinity

Question 6. A correlation coefficient of +1 indicates a perfect __________ linear correlation.

(A) Negative

(B) Positive

(C) Zero

(D) Non-linear

Question 7. A correlation coefficient of 0 indicates __________ linear correlation between the two variables.

(A) Perfect

(B) Strong

(C) Weak

(D) No

Question 8. Spearman's Rank Correlation Coefficient is used when the data is in the form of __________ or the relationship is monotonic.

(A) Frequencies

(B) Percentages

(C) Ranks

(D) Raw scores

Question 9. Correlation does NOT imply __________; it only shows association.

(A) Relationship

(B) Causation

(C) Covariation

(D) Dependence

Question 10. The strength of a linear relationship is indicated by the __________ of the correlation coefficient (its absolute value).

(A) Sign

(B) Direction

(C) Magnitude

(D) Unit

Question 1. Probability is a numerical measure of the __________ of an event occurring.

(A) Outcome

(B) Certainty

(C) Likelihood

(D) Frequency

Question 2. An experiment whose outcome cannot be predicted with certainty but all possible outcomes are known is called a __________ experiment.

(A) Certain

(B) Deterministic

(C) Random

(D) Simple

Question 3. The set of all possible outcomes of a random experiment is called the Sample __________.

(A) Point

(B) Event

(C) Space

(D) Outcome

Question 4. A subset of the sample space is called an____

(A) Outcome

(B) Event

(C) Experiment

(D) Probability

Question 5. An event consisting of a single outcome is called a __________ event.

(A) Compound

(B) Simple

(C) Impossible

(D) Sure

Question 6. Two events are said to be mutually exclusive if they cannot occur __________ in a single trial.

(A) Independently

(B) Simultaneously

(C) Randomly

(D) Theoretically

Question 7. According to the classical definition, probability is the ratio of the number of __________ outcomes to the total number of possible outcomes.

(A) Random

(B) Uncertain

(C) Favorable

(D) Experimental

Question 8. The range of probability for any event E is between 0 and 1, inclusive, meaning $0 \le P(E) \le$ __________.

(A) 0

(B) 0.5

(C) 1

(D) Infinity

Question 9. Experimental probability is based on the actual results observed from conducting an experiment a certain number of____, unlike theoretical probability.

(A) Outcomes

(B) Events

(C) Trials

(D) Probabilities

Question 10. As the number of trials in an experiment increases, the experimental probability of an event tends to approach its __________ probability.

(A) Subjective

(B) Conditional

(C) Impossible

(D) Theoretical (Classical)

Question 1. The axiomatic approach to probability defines probability based on a set of fundamental rules called __________.

(A) Theorems

(B) Laws

(C) Axioms

(D) Formulas

Question 2. According to the axioms, the probability of any event A must be non-negative, and the probability of the sample space must be equal to __________.

(A) 0

(B) 0.5

(C) 1

(D) The total number of outcomes

Question 3. The Law of Complementary Events states that the probability of an event A not occurring ($A'$) is equal to 1 minus the probability of A occurring, i.e., $P(A') = 1 -$ __________.

(A) $P(A')$

(B) $P(A)$

(C) 0

(D) 1

Question 4. For any two mutually exclusive events A and B, the probability that A or B occurs is given by the Addition Law as $P(A \cup B) = P(A) +$ __________.

(A) $P(B)$

(B) $P(A \cap B)$

(C) $P(A|B)$

(D) $P(B|A)$

Question 5. The general Addition Law for any two events A and B (not necessarily mutually exclusive) is $P(A \cup B) = P(A) + P(B) -$ __________.

(A) $P(A \cup B)$

(B) $P(A \cap B)$

(C) $P(A|B)$

(D) $P(B|A)$

Question 6. If $P(A)=0.4$ and $P(A \cup B)=0.7$. If A and B are mutually exclusive, then $P(B)$ is __________.

(A) $0.7 - 0.4 = 0.3$ (Since $P(A \cup B) = P(A) + P(B)$ for mutually exclusive events)

(B) $0.7 + 0.4 = 1.1$

(C) $0.4 \times 0.7 = 0.28$

(D) 0.3

Question 7. If $P(A)=0.5, P(B)=0.6$, and $P(A \cap B)=0.2$. Then $P(A \cup B)$ is __________.

(A) $0.5 + 0.6 = 1.1$

(B) $0.5 + 0.6 - 0.2 = 0.9$

(C) 0.9

(D) 0.2

Question 8. The axiomatic approach provides a mathematical foundation for probability theory from which the laws of probability are __________.

(A) Assumed

(B) Defined

(C) Derived

(D) Calculated experimentally

Question 9. For any event A, $P(A) + P(A') = $ __________.

(A) 0

(B) 0.5

(C) 1

(D) $P(A \cap A')$

Question 10. If A and B are mutually exclusive, then $P(A \cap B) = $ __________.

(A) $P(A)P(B)$

(B) $P(A) + P(B)$

(C) 0

(D) 1

Question 1. The probability of event A occurring given that event B has already occurred is denoted by __________.

(A) $P(A \cap B)$

(B) $P(A \cup B)$

(C) $P(A|B)$

(D) $P(B|A)$

Question 2. The formula for conditional probability $P(A|B)$ is $\frac{P(A \cap B)}{\text{__________}}$, provided the denominator is not zero.

(A) $P(A)$

(B) $P(B)$

(C) $P(A \cup B)$

(D) $P(A \cap B)$

Question 3. If A and B are independent events and $P(B) \neq 0$, then $P(A|B) = $ __________.

(A) $P(B)$

(B) $P(A)$

(C) $P(A \cap B)$

(D) $P(A)/P(B)$

Question 4. If A and B are mutually exclusive events and $P(B) \neq 0$, then $P(A|B) = $ __________.

(A) 1

(B) 0

(C) $P(A)$

(D) $P(B)$

Question 5. If $P(A \cap B) = 0.4$ and $P(B) = 0.8$, then $P(A|B) = $ __________.

(A) $0.4 / 0.8 = 0.5$

(B) $0.8 / 0.4 = 2$

(C) 0.5

(D) 0.4

Question 6. The probability of 'A and B' ($P(A \cap B)$) can be calculated using the Multiplication Law as $P(A|B) \times$ __________.

(A) $P(A)$

(B) $P(B)$

(C) $P(A|B)$

(D) $P(A \cup B)$

Question 7. If $P(A|B) = P(A)$, assuming $P(A) > 0$ and $P(B) > 0$, then events A and B are __________.

(A) Mutually exclusive

(B) Dependent

(C) Independent

(D) Conditional

Question 8. For any event A and any conditioning event B with $P(B) \neq 0$, $P(A|B) + P(A'|B) = $ __________.

(A) 0

(B) 0.5

(C) 1

(D) $P(A)$

Question 9. Conditional probability is a fundamental concept for understanding the probability of events when their occurrences are __________.

(A) Equal

(B) Random

(C) Unrelated

(D) Related or dependent

Question 10. If $P(A|B) = 1$ and $P(B) \neq 0$, it means that if event B occurs, event A must __________.

(A) Not occur

(B) Also occur

(C) Be independent

(D) Be mutually exclusive

Question 1. The Multiplication Theorem on Probability states that the probability of the intersection of two events A and B is $P(A \cap B) =$ __________ or $P(A \cap B) =$ __________.

(A) $P(A)P(B|A)$, $P(B)P(A|B)$

(B) $P(A)+P(B)$, $P(A)P(B)$

(C) $P(A \cup B)$, $P(A)P(B)$

(D) $P(A)+P(B|A)$, $P(B)+P(A|B)$

Question 2. Two events A and B are defined as independent if the occurrence of one does not affect the __________ of the other.

(A) Outcome

(B) Frequency

(C) Probability

(D) Sample space

Question 3. Events A and B are independent if and only if $P(A \cap B) =$ __________.

(A) $P(A)+P(B)$

(B) $P(A \cup B)$

(C) $P(A)P(B)$

(D) 0

Question 4. Drawing two cards from a deck *with replacement* makes the outcome of the second draw __________ of the first draw.

(A) Dependent

(B) Mutually exclusive

(C) Independent

(D) Conditional

Question 5. Drawing two cards from a deck *without replacement* makes the outcome of the second draw __________ on the first draw.

(A) Dependent

(B) Independent

(C) Mutually exclusive

(D) Random

Question 6. A collection of events $E_1, E_2, ____, E_n$ forms a partition of the sample space if they are mutually exclusive and __________.

(A) Independent

(B) Dependent

(C) Exhaustive (their union is the sample space)

(D) Equally likely

Question 7. The Law of Total Probability states that if $E_1, ____, E_n$ is a partition, $P(A) = \sum_{i=1}^n$ __________.

(A) $P(E_i|A)P(E_i)$

(B) $P(A|E_i)P(A)$

(C) $P(A|E_i)P(E_i)$

(D) $P(A \cap E_i)$ or $P(A|E_i)P(E_i)$

Question 8. If $P(A)=0.4$ and $P(B)=0.5$. If A and B are independent, then $P(A \cap B) = $ __________.

(A) $0.4 + 0.5 = 0.9$

(B) $0.4 \times 0.5 = 0.2$

(C) 0.2

(D) 0

Question 9. The Law of Total Probability is useful for calculating the probability of an event by considering all the mutually exclusive __________ under which it can occur.

(A) Outcomes

(B) Experiments

(C) Conditions (Partitioning Events)

(D) Unions

Question 10. If events A and B are mutually exclusive and $P(A)>0, P(B)>0$, they cannot be __________.

(A) Mutually exclusive (This contradicts the premise)

(B) Exhaustive

(C) Independent

(D) Conditional

Question 1. Bayes’ Theorem provides a formula to calculate the probability of a __________ given some observed evidence.

(A) Sample space

(B) Prior probability

(C) Cause or hypothesis

(D) Likelihood

Question 2. In the formula $P(A|B) = \frac{P(B|A)P(A)}{P(B)}$, $P(A|B)$ is called the __________ probability of A given B.

(A) Prior

(B) Marginal

(C) Joint

(D) Posterior

Question 3. In the formula $P(A|B) = \frac{P(B|A)P(A)}{P(B)}$, $P(B|A)$ is called the __________ of the evidence B given A is true.

(A) Prior

(B) Posterior

(C) Likelihood

(D) Marginal

Question 4. Bayes' Theorem is an extension of the concept of __________ probability.

(A) Marginal

(B) Joint

(C) Conditional

(D) Independent

Question 5. The denominator $P(B)$ in Bayes' Theorem is the marginal probability of the evidence and can be calculated using the Law of Total __________.

(A) Events

(B) Probability

(C) Partitions

(D) Unions

Question 6. Bayes' Theorem is widely used in applications where probabilities need to be __________ based on new data.

(A) Ignored

(B) Simplified

(C) Updated or revised

(D) Calculated from scratch

Question 7. In the general form of Bayes' Theorem involving a partition $E_1, ____, E_n$, the term $P(E_i)$ in the numerator is the __________ probability of $E_i$.

(A) Posterior

(B) Conditional

(C) Prior

(D) Joint

Question 8. Bayes' Theorem provides a mathematical framework for __________ inference, where beliefs are updated as more evidence becomes available.

(A) Frequentist

(B) Classical

(C) Empirical

(D) Bayesian

Question 9. If $P(A|B) > P(A)$, it suggests that the occurrence of event B makes event A __________ likely.

(A) Less

(B) Equally

(C) More

(D) Not at all

Question 10. The application of Bayes' Theorem requires knowing the prior probabilities of the hypotheses and the __________ of the evidence under each hypothesis.

(A) Posterior probabilities

(B) Marginal probabilities

(C) Likelihoods

(D) Joint probabilities

Question 1. A function that assigns a real number to each outcome in the sample space of a random experiment is called a random __________.

(A) Outcome

(B) Event

(C) Function

(D) Variable

Question 2. A random variable that can take only a finite or countably infinite number of distinct values is called a __________ random variable.

(A) Continuous

(B) Qualitative

(C) Discrete

(D) Deterministic

Question 3. A random variable that can take any value within a given range or interval is called a __________ random variable.

(A) Discrete

(B) Categorical

(C) Continuous

(D) Countable

Question 4. The number of heads obtained in 4 coin tosses is an example of a __________ random variable.

(A) Continuous

(B) Discrete

(C) Qualitative

(D) Interval

Question 5. The temperature of a city at noon is an example of a __________ random variable.

(A) Discrete

(B) Categorical

(C) Continuous

(D) Countable

Question 6. A probability distribution describes the probability of a random variable taking each of its possible __________ or falling within a range.

(A) Frequencies

(B) Values

(C) Outcomes

(D) Events

Question 7. For a valid probability distribution of a discrete random variable, the probability of each possible value must be between 0 and 1, and the sum of all probabilities must equal __________.

(A) 0

(B) 0.5

(C) 1

(D) The number of values

Question 8. The probability distribution of a discrete random variable is described by its Probability Mass __________ (PMF).

(A) Function

(B) Density

(C) Table

(D) Value

Question 9. For a continuous random variable, the probability of it taking any single specific value is always __________.

(A) 0

(B) 0.5

(C) 1

(D) Greater than 0

Question 10. For a continuous random variable, probability is measured by the area under the curve of its Probability Density __________ (PDF).

(A) Mass

(B) Function

(C) Distribution

(D) Value

Question 1. The Mathematical Expectation $E(X)$ of a random variable X is also known as its theoretical __________.

(A) Median

(B) Mode

(C) Mean

(D) Variance

Question 2. For a discrete random variable X, the expected value is calculated as the sum of each possible value multiplied by its corresponding __________.

(A) Frequency

(B) Cumulative frequency

(C) Probability

(D) Class mark

Question 3. The Variance of a random variable measures the __________ or dispersion of its distribution.

(A) Center

(B) Shape

(C) Spread

(D) Frequency

Question 4. The Variance of a random variable X is calculated as the expected value of the squared __________ from the mean $E[(X - E(X))^2]$.

(A) Values

(B) Outcomes

(C) Frequencies

(D) Deviations

Question 5. The Standard Deviation of a random variable is the __________ square root of its Variance.

(A) Negative

(B) Positive

(C) Square

(D) Cube

Question 6. If X is a random variable and 'a' is a constant, then $E(aX) = $ __________ $E(X)$.

(A) +a

(B) -a

(C) a

(D) $a^2$

Question 7. If X is a random variable and 'b' is a constant, then $Var(X + b) = $ __________.

(A) $Var(X) + b$

(B) $Var(X)$

(C) $Var(X) + b^2$

(D) $b Var(X)$

Question 8. The expected value represents the long-run __________ value of the random variable if the experiment is repeated many times.

(A) Maximum

(B) Minimum

(C) Average

(D) Random

Question 9. If $Var(X) = 0$, it means the random variable X is a __________.

(A) Discrete variable

(B) Continuous variable

(C) Constant

(D) Random outcome

Question 10. The units of the Standard Deviation of a random variable are the __________ as the units of the random variable itself.

(A) Same

(B) Square

(C) Square root

(D) Different

Question 1. A sequence of independent trials, each with only two possible outcomes (Success or Failure), is called a series of __________ trials.

(A) Random

(B) Dependent

(C) Binomial

(D) Bernoulli

Question 2. The number of successes in a fixed number of independent Bernoulli trials follows a __________ distribution.

(A) Poisson

(B) Normal

(C) Binomial

(D) Uniform

Question 3. The two parameters that define a specific Binomial distribution are the number of trials (n) and the probability of __________ (p).

(A) Failure

(B) Outcome

(C) Success

(D) Occurrence

Question 4. For a Binomial distribution with parameters n and p, the mean is given by the formula __________.

(A) np

(B) np(1-p)

(C) $\sqrt{np(1-p)}$

(D) n/p

Question 5. For a Binomial distribution with parameters n and p, the variance is given by the formula __________.

(A) np

(B) np(1-p)

(C) $\sqrt{np(1-p)}$

(D) np/(1-p)

Question 6. The possible values that a Binomial random variable can take are the integers from 0 to __________.

(A) p

(B) 1

(C) k

(D) n

Question 7. The Binomial distribution is symmetric when the probability of success (p) is equal to __________.

(A) 0

(B) 1

(C) 0.5

(D) n

Question 8. As the number of trials (n) becomes large, and p is not too close to 0 or 1, the Binomial distribution can be approximated by the __________ distribution.

(A) Poisson

(B) Uniform

(C) Exponential

(D) Normal

Question 9. The probability mass function for a Binomial distribution gives the probability of getting exactly __________ successes in n trials.

(A) p

(B) n

(C) k

(D) q

Question 10. The square root of the variance of a Binomial distribution is called its Standard __________.

(A) Error

(B) Mean

(C) Deviation

(D) Probability

Question 1. The Poisson distribution is a __________ probability distribution used to model the number of occurrences of events in a fixed interval.

(A) Continuous

(B) Discrete

(C) Categorical

(D) Uniform

Question 2. The key parameter of the Poisson distribution, denoted by $\lambda$, represents the average __________ of occurrence in the given interval.

(A) Number

(B) Probability

(C) Rate

(D) Frequency

Question 3. For a Poisson distribution with parameter $\lambda$, both the Mean and the Variance are equal to __________.

(A) $\sqrt{\lambda}$

(B) $\lambda^2$

(C) $\lambda$

(D) $e^{-\lambda}$

Question 4. The possible values that a Poisson random variable can take are the non-negative __________ (0, 1, 2, ____).

(A) Real numbers

(B) Decimals

(C) Integers

(D) Fractions

Question 5. The probability mass function for a Poisson distribution with parameter $\lambda$ is $P(X=k) = \frac{e^{-\lambda} \lambda^k}{\text{__________}}$.

(A) $\lambda!$

(B) $k!$

(C) $\lambda^k$

(D) $e^k$

Question 6. The Poisson distribution is often used to model events that are considered __________ occurrences in a large number of trials or over a continuous interval.

(A) Frequent

(B) Rare

(C) Predictable

(D) Dependent

Question 7. The Poisson distribution can be used as an approximation to the Binomial distribution when the number of trials (n) is large and the probability of success (p) is __________.

(A) Large

(B) Moderate

(C) Small

(D) 0.5

Question 8. For small values of $\lambda$, the Poisson distribution is skewed, but as $\lambda$ increases, it becomes more __________ and approaches the Normal distribution.

(A) Positively skewed

(B) Negatively skewed

(C) Peaked

(D) Symmetric

Question 9. The standard deviation of a Poisson distribution is the square root of its __________.

(A) Mean

(B) Variance

(C) Parameter $\lambda$

(D) All of the above

Question 10. A key assumption for the Poisson distribution is that the events occur __________ of each other.

(A) Densely

(B) Collectively

(C) Independently

(D) Uniformly

Question 1. The Normal distribution is a __________ probability distribution.

(A) Discrete

(B) Continuous

(C) Categorical

(D) Ordinal

Question 2. The graph of the Normal distribution is symmetric and __________-shaped.

(A) Square

(B) Rectangular

(C) Bell

(D) Triangular

Question 3. In a Normal distribution, the Mean, Median, and Mode are all located at the __________ and are equal in value.

(A) Tails

(B) Peak (Center)

(C) Origin

(D) Boundaries

Question 4. The two parameters that completely define a specific Normal distribution are the Mean ($\mu$) and the Standard __________ ($\sigma$).

(A) Frequency

(B) Deviation

(C) Variance

(D) Range

Question 5. The Standard Normal distribution has a mean of __________ and a standard deviation of __________.

(A) 0, 1

(B) 1, 0

(C) $\mu, \sigma$

(D) $\bar{x}, s$

Question 6. A z-score measures how many __________ standard deviations a value is away from the mean.

(A) Units

(B) Mean

(C) Variance

(D) Standard

Question 7. The total area under the curve of the Standard Normal distribution is equal to __________.

(A) 0

(B) 0.5

(C) 1

(D) $\infty$

Question 8. In a Normal distribution, approximately 68% of the data falls within __________ standard deviation of the mean.

(A) 1

(B) 2

(C) 3

(D) 0.5

Question 9. The tails of the Normal distribution curve extend infinitely in both directions and approach the x-axis __________.

(A) Abruptly

(B) Asymptotically (without touching)

(C) Linearly

(D) Rapidly

Question 10. The Normal distribution is crucial due to the Central Limit Theorem, which states that the distribution of sample means approaches normality as the sample size __________.

(A) Decreases

(B) Remains constant

(C) Increases

(D) Becomes symmetric

Question 1. The entire group of individuals or objects that a researcher is interested in studying is called the __________.

(A) Sample

(B) Statistic

(C) Population

(D) Parameter

Question 2. A subset drawn from the population for the purpose of study is called a __________.

(A) Population

(B) Parameter

(C) Statistic

(D) Sample

Question 3. A numerical characteristic of the population, such as the population mean ($\mu$), is called a __________.

(A) Statistic

(B) Sample

(C) Parameter

(D) Data point

Question 4. A numerical characteristic calculated from sample data, such as the sample mean ($\bar{x}$), is called a __________.

(A) Parameter

(B) Population

(C) Statistic

(D) Observation

Question 5. Inferential statistics involves using sample data to make __________ about population parameters.

(A) Certainties

(B) Guesses or inferences

(C) Descriptions

(D) Calculations

Question 6. We often study a sample instead of the entire population because studying the population can be too costly, time-consuming, or __________.

(A) Practical

(B) Unrealistic

(C) Representative

(D) Simple

Question 7. The process of selecting a sample from a population is called __________.

(A) Analysis

(B) Interpretation

(C) Sampling

(D) Parameter estimation

Question 8. Ideally, a sample should be __________ of the population to ensure that the inferences made are valid.

(A) Biased

(B) Identical

(C) Representative

(D) Larger

Question 9. Sampling variability refers to the natural __________ in statistics calculated from different samples drawn from the same population.

(A) Consistency

(B) Bias

(C) Variation

(D) Predictability

Question 10. A census involves collecting data from the entire __________.

(A) Sample

(B) Parameter

(C) Statistic

(D) Population

Question 1. Statistical inference uses sample data to make conclusions about the population, accounting for the inherent __________ in sampling.

(A) Certainty

(B) Bias

(C) Variability or uncertainty

(D) Precision

Question 2. Hypothesis testing is a statistical procedure used to test a claim or __________ about a population parameter.

(A) Statistic

(B) Sample

(C) Hypothesis

(D) Observation

Question 3. The hypothesis that states there is no significant difference or effect is called the __________ hypothesis ($H_0$).

(A) Alternative

(B) Research

(C) Null

(D) Statistical

Question 4. The hypothesis that contradicts the null hypothesis, suggesting a significant difference or effect, is the __________ hypothesis ($H_1$ or $H_a$).

(A) Null

(B) Alternative

(C) Status quo

(D) Conservative

Question 5. A Type I Error occurs when the null hypothesis is rejected when it is actually __________.

(A) False

(B) True

(C) Uncertain

(D) Significant

Question 6. The probability of making a Type I Error is denoted by $\alpha$ and is called the level of __________.

(A) Power

(B) Confidence

(C) Significance

(D) Error

Question 7. A Type II Error occurs when you fail to reject the null hypothesis when it is actually __________.

(A) True

(B) False

(C) Accepted

(D) Significant

Question 8. The P-value is the probability of obtaining a test statistic as extreme as, or more extreme than, the one observed, assuming the __________ hypothesis is true.

(A) Alternative

(B) Research

(C) Null

(D) Statistical

Question 9. If the p-value is less than or equal to the level of significance ($\alpha$), we __________ the null hypothesis.

(A) Fail to reject

(B) Accept

(C) Support

(D) Reject

Question 10. A test that examines whether a population parameter is different from a specific value ($\neq$) is called a __________-tailed test.

(A) One

(B) Two

(C) Left

(D) Right

Question 1. The t-distribution is similar to the Normal distribution but has __________ tails, especially for small degrees of freedom.

(A) Thinner

(B) Fatter

(C) Skewed

(D) Symmetric

Question 2. The shape of the t-distribution depends on the __________ of freedom.

(A) Sample size

(B) Population mean

(C) Degrees

(D) Standard deviation

Question 3. As the degrees of freedom increase, the t-distribution approaches the __________ Normal distribution.

(A) Standard

(B) Skewed

(C) Uniform

(D) Poisson

Question 4. A one-sample t-test is used to compare the mean of a single sample to a known or hypothesized population mean when the population standard deviation is __________.

(A) Known

(B) Equal to sample SD

(C) Zero

(D) Unknown

Question 5. The degrees of freedom for a one-sample t-test with sample size n is __________.

(A) n

(B) $n-1$

(C) $n-2$

(D) n/2

Question 6. A two independent groups t-test is used to compare the means of two samples that are __________ of each other.

(A) Dependent

(B) Paired

(C) Related

(D) Independent

Question 7. The degrees of freedom for a two independent samples t-test with sample sizes $n_1$ and $n_2$ (assuming equal variances) is __________.

(A) $n_1 + n_2$

(B) $n_1 + n_2 - 1$

(C) $n_1 + n_2 - 2$

(D) min($n_1, n_2$) - 1

Question 8. A paired samples t-test is used when comparing the means of two __________ samples, such as before-and-after measurements on the same individuals.

(A) Independent

(B) Unrelated

(C) Dependent

(D) Random

Question 9. When using a t-test, a key assumption is that the data is sampled from a population that is approximately __________ distributed.

(A) Uniformly

(B) Poisson

(C) Normally

(D) Exponentially

Question 10. For large sample sizes, the results of a t-test are very similar to those of a __________-test.

(A) F

(B) Chi-square

(C) Z

(D) ANOVA