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PBSI 301: STATS > Benchmark Practice Questions > Flashcards

Benchmark Practice Questions Flashcards

1
Q

What is the purpose of statistics in research?
A) To make data look more appealing
B) To collect, analyze, interpret, and present empirical data
C) To develop mathematical models for theoretical physics
D) To eliminate all errors in research findings

A

B) To collect, analyze, interpret, and present empirical data

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2
Q

Which of the following best describes the field of statistics?
A) A branch of mathematics focused on numerical computation
B) A discipline concerned only with data collection
C) The science of developing methods for handling empirical data
D) A set of formulas used exclusively in business analytics

A

C) The science of developing methods for handling empirical data

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3
Q

What is the most common goal of statistics?
A) To collect data from the entire population
B) To organize and present data in visual formats
C) To use information from a sample to make inferences about a
population
D) To eliminate all variability in data

A

C) To use information from a sample to make inferences about a
population

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4
Q

Which of the following best distinguishes inferential statistics
from descriptive statistics?
A) Inferential statistics focuses on summarizing the dataset.
B) Descriptive statistics uses sample data to make predictions
about a population.
C) Inferential statistics involves making generalizations about a
population based on sample data.
D) Descriptive statistics eliminates random error in datasets.

A

C) Inferential statistics involves making generalizations about a
population based on sample data.

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5
Q

Which of the following is an example of qualitative data?
A) The weight of a group of people in kilograms
B) The number of hours spent studying in a week C) The blood type of patients (A, B, AB, O)
D) The distance traveled in miles

A

C) The blood type of patients (A, B, AB, O)

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6
Q

What distinguishes quantitative data from qualitative data?
A) Quantitative data are always descriptive, while
qualitative data are numerical.
B) Quantitative data involve numbers, while qualitative data
classify entities into categories.
C) Quantitative data are fixed, while qualitative data can
take any value.
D) Quantitative data are always categorical, while
qualitative data are continuous.

A

B) Quantitative data involve numbers, while qualitative data
classify entities into categories.

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7
Q

What does correlation imply?
A) One variable causes the other to change
B) There is a statistical association between two variables
C) Both variables are independent of each other
D) A causal relationship always exists

A

B) There is a statistical association between two variables

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8
Q

Which measure of central tendency is
most affected by extreme values?
A) Mean
B) Median
C) Mode
D) Same

A

A) Mean

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9
Q

When is the median a better measure of
central tendency than the mean?
A) When the dataset has no extreme values
B) When the dataset is symmetric
C) When the dataset is skewed or contains outliers
D) When the mode is not calculable

A

C) When the dataset is skewed or contains outliers

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10
Q

Which measure of variability is calculated as the difference between the highest and lowest values?
A) Range
B) Standard Deviation
C) Variance
D) Median

A

A) Range

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11
Q

What does a small standard deviation indicate about a dataset? A) The data points are spread out widely.
B) The data points are close to the mean.
C) The dataset has extreme values.
D) The dataset is categorical.

A

B) The data points are close to the mean.

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12
Q

What is the primary purpose of variance in a dataset?
A) To measure the central value.
B) To indicate the presence of extreme values.
C) To quantify the average squared deviation from the mean.
D) To identify the most frequent value.

A

C) To quantify the average squared deviation from the mean.

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13
Q

What is a common method to identify extreme values in a dataset?
A) Calculate the mean and median
B) Use box plots
C) Measure the range of the dataset
D) Find the mode of the data

A

B) Use box plots

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14
Q

What is the primary purpose of a histogram?
A) To compare two datasets.
B) To display the relationship between two variables.
C) To visualize the distribution of continuous data.
D) To calculate the mean of a dataset.

A

C) To visualize the distribution of continuous data.

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15
Q

What does skewness measure in a dataset?
A) The central tendency of the data.
B) The asymmetry of the data distribution.
C) The variability of the data.
D) The sharpness of the peak of the data distribution.

A

B) The asymmetry of the data distribution.

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16
Q

What does a scatterplot display?
A) The relationship between two categorical variables.
B) The relationship between two numeric variables.
C) The frequency of data in intervals.
D) The central tendency of a dataset.

A

B) The relationship between two numeric variables.

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17
Q

What does reliability refer to in statistics?
A) The accuracy of a measurement.
B) The stability and consistency of a measurement.
C) The ability to measure what is claimed.
D) The generalizability of a study’s findings.

A

B) The stability and consistency of a measurement.

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18
Q

What does validity in a measurement refer to?
A) Producing consistent results over time.
B) The extent to which the measure appears appropriate to non-experts.
C) Measuring what it is intended to measure.
D) The ability of multiple observers to agree on a judgment.

A

C) Measuring what it is intended to measure.

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19
Q

Which of the following is TRUE about reliability and validity?
A) A measure can be valid but not reliable.
B) A measure can be reliable but not valid.
C) A measure must be reliable to be valid.
D) Both A and B are correct.

A

D) Both A and B are correct.

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20
Q

What does a measure with high validity but low reliability look like?
A) Always hits the wrong target consistently.
B) Targets the correct concept but produces inconsistent results.
C) Produces inconsistent results and measures the wrong concept.
D) Consistently measures the correct concept.

A

B) Targets the correct concept but produces inconsistent results.

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21
Q

What type of validity is being assessed when the scores of a depression test are compared with clinical diagnoses of depression?
A) Face Validity
B) Construct Validity
C) Criterion-Related Validity
D) Content Validity

A

C) Criterion-Related Validity

22
Q

A teacher gives the same math test to students twice, one month
apart, to see if the scores are consistent over time.
What type of reliability is being assessed?
A) Internal Consistency
B) Test-Retest Reliability
C) Interrater Reliability
D) Criterion Validity

A

B) Test-Retest Reliability

23
Q

What is the logic of hypothesis testing in statistics?
A) To prove the null hypothesis is true.
B) To determine if there is enough evidence to reject the null hypothesis.
C) To identify the mean of the population.
D) To calculate the variability of the data.

A

B) To determine if there is enough evidence to reject the null hypothesis.

24
Q

What is a Type I error in hypothesis testing?
A) Rejecting the null hypothesis when it is true.
B) Failing to reject the null hypothesis when it is false. C) Accepting the alternative hypothesis when it is false.
D) Rejecting the alternative hypothesis when it is true.

A

A) Rejecting the null hypothesis when it is true.

25
Q

What is a Type II error in hypothesis testing?
A) Rejecting the null hypothesis when it is true. B) Failing to reject the null hypothesis when it is false. C) Accepting the null hypothesis when it is true. D) Accepting the alternative hypothesis when it is false.

A

B) Failing to reject the null hypothesis when it is false.

26
Q

What is a critical value in hypothesis testing?
A) The threshold for rejecting the null hypothesis.
B) The actual test statistic calculated from the data. C) The probability of a Type I error occurring.
D) The midpoint of the confidence interval.

A

A) The threshold for rejecting the null hypothesis.

27
Q

In a hypothesis test, if the test statistic exceeds the critical
value, what should be done?
A) Fail to reject the null hypothesis.
B) Reject the null hypothesis.
C) Accept the alternative hypothesis directly.
D) Increase the sample size.

A

B) Reject the null hypothesis.

28
Q

What does the null hypothesis (H₀) represent? A) The statement that there is an effect or difference.
B) The assumption that there is no effect or difference.
C) The researcher’s belief about the outcome.
D) The probability of rejecting the null hypothesis.

A

B) The assumption that there is no effect or difference.

29
Q

Which of the following is an example of a research
hypothesis (H₁)?
A) H₁: The mean (μ) equals 5.
B) H₁: The mean (μ) is not equal to 5.
C) H₁: The proportion (p) equals 0.3.
D) H₁: The variance (σ²) equals 25.

A

B) H₁: The mean (μ) is not equal to 5.

30
Q

Which of the following is an example of a research hypothesis
(H₁)?
A) H₁: The mean (μ) equals 5.
B) H₁: The mean (μ) is not equal to 5.
C) H₁: The proportion (p) equals 0.3.
D) H₁: The variance (σ²) equals 25.

A

B) H₁: The mean (μ) is not equal to 5.

31
Q

What does the power of a statistical test refer to?
A) The probability of rejecting the null hypothesis when it is false. B) The probability of rejecting the null hypothesis when it is true. C) The ability to detect a Type I error.
D) The significance level of the test.

A

A) The probability of rejecting the null hypothesis when it is false.

32
Q

If the p-value of a test is less than the significance level (α),
what conclusion can you draw?
A) Fail to reject the null hypothesis.
B) Reject the null hypothesis.
C) Accept the null hypothesis.
D) Increase the sample size to confirm the result.

A

B) Reject the null hypothesis.

33
Q

Which of the following is true about the tails of the normal
distribution?
A) They eventually touch the horizontal axis.
B) They approach but never touch the horizontal axis.
C) They extend to infinity.
D) Both B and C.

A

D) Both B and C.

34
Q

The total area under the curve of a normal distribution is equal
to:
A) 0
B) 1
C) π\piπ
D) Infinity

A

B) 1

35
Q

The central value of a normal distribution corresponds to:
A) The smallest value.
B) The highest frequency value.
C) The most extreme value.
D) The cumulative probability.

A

B) The highest frequency value.

36
Q

A researcher conducts a 2 × 3 Factorial ANOVA. How many main effects can
they analyze?
A) 1
B) 2
C) 3
D) 5

A

B) 2

37
Q

A researcher is analyzing test scores across Teaching Method (Online, Inperson: 2 levels), Class Size (Large, Medium, Small: 3 levels), and Course Subject (Economics, Psychology, Politics: 3 levels). What type of ANOVA is appropriate?
A) 2 × 3 One-Way ANOVA
B) 2 × 3 Two-Way Factorial ANOVA
C) 2 × 3 × 3 Three-Way Factorial ANOVA
D) None of the above

A

C) 2 × 3 × 3 Three-Way Factorial ANOVA

38
Q

A researcher is studying the impact of different diets (Low-Carb, Low-Fat,
Mediterranean) on weight loss. What type of ANOVA is appropriate?
A) One-Way ANOVA
B) 1 × 3 Two-Way ANOVA C) Three-Way Factorial ANOVA
D) None of the above

A

A) One-Way ANOVA

39
Q

What does correlation measure?
A) The strength and direction of a linear relationship
between two variables.
B) The change in one variable relative to another without
direction.
C) The variability of a single variable.
D) The non-linear relationship between two variables.

A

A) The strength and direction of a linear relationship
between two variables.

40
Q

Which of the following statements about correlation is
true?
A) Correlation has no upper or lower limits.
B) Correlation is unaffected by the scale of the variables.
C) Correlation measures only the direction of a
relationship.
D) Correlation is always positive.

A

B) Correlation is unaffected by the scale of the variables.

41
Q

Which example best illustrates a negative correlation?
A) Higher temperatures are associated with higher ice
cream sales.
B) More hours of study are associated with higher
grades.
C) As exercise time increases, weight decreases.
D) More rainfall leads to more plant growth.

A

C) As exercise time increases, weight decreases.

42
Q

If the correlation coefficient (r) is -0.85, what does this
imply?
A) A weak negative linear relationship.
B) A strong positive linear relationship.
C) A strong negative linear relationship.
D) No relationship between the variables.

A

C) A strong negative linear relationship.

43
Q

Which limitation of correlation occurs when a small
subset of the population is studied?
A) Sensitivity to outliers
B) Curvilinear relationships C) Restriction of range
D) Independence of variables

A

C) Restriction of range

44
Q

If the correlation between two variables is near zero, but a scatterplot shows a clear U-shaped pattern, this indicates:
A) A weak linear relationship.
B) No relationship between the variables.
C) A curvilinear relationship that correlation fails to
capture.
D) A perfect negative relationship.

A

C) A curvilinear relationship that correlation fails to
capture.

45
Q

A researcher wants to determine if there is a relationship between gender (Male, Female) and preference for a type of vacation (Beach,
Mountains, City). Which test should they use?
A) One-Way ANOVA
B) Chi-Squared Test of Independence
C) Chi-Squared Goodness-of-Fit Test
D) Independent t-Test

A

B) Chi-Squared Test of Independence

46
Q

A company surveys employees to see if the number
of people choosing different lunch options
(Sandwiches, Salads, Fast Food) matches their predicted distribution. What test should they use? A) Chi-Squared Goodness-of-Fit Test
B) Chi-Squared Test of Independence
C) One-Way ANOVA
D) Correlation Analysis

A

A) Chi-Squared Goodness-of-Fit Test

47
Q

Which of the following best defines residuals in a regression model?
A) The predicted value of the dependent variable for a given X.
B) The difference between the observed Y and predicted Y.
C) The percentage of variation explained by the independent variables. * D) The slope of the regression line.

A

B) The difference between the observed Y and predicted Y.

48
Q

If the R-Squared value of a model is 0.85, what does this indicate?
A) 85% of the variation in Y is explained by the independent variable(s). B) 85% of the data points lie on the regression line.
C) The residuals have an average magnitude of 0.85.
D) The slope of the line is 0.85.

A

A) 85% of the variation in Y is explained by the independent variable(s).

49
Q

What does a slope of -2 mean in a regression model?
A) Y increases by 2 units for every 1 unit increase in X.
B) Y decreases by 2 units for every 1 unit increase in X.
C) The intercept of the regression line is -2.
D) The residuals are decreasing by 2.

A

B) Y decreases by 2 units for every 1 unit increase in X.

50
Q

What does it mean if the intercept in a regression equation is 5?
A) The slope of the line is 5.
B) Y is predicted to be 5 when X is 0.
C) The difference between observed and predicted values is 5.
D) The regression line crosses the X-axis at 5.

A

B) Y is predicted to be 5 when X is 0.

51
Q

What is indicated if the residual for a particular observation is 0?
A) The predicted value is equal to the observed value.
B) The regression model explains 0% of the variation.
C) The observed value is less than the predicted value.
D) The independent variable has no effect on the dependent variable

A

A) The predicted value is equal to the observed value.

52
Q

What does a high R-Squared value imply about a regression model?
A) The model is free of errors.
B) The model perfectly fits the data.
C) The independent variable(s) explain a large proportion of the variation in Y.
D) The residuals are normally distributed.

A

C) The independent variable(s) explain a large proportion of the variation in Y.

PBSI 301: STATS (2 decks)

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