Inferential Statistics MCQs
Inferential Statistics MCQs
These Inferential Statistics multiple-choice questions and their answers will help you strengthen your grip on the subject of Inferential Statistics. You can prepare for an upcoming exam or job interview with these Inferential Statistics MCQs.
So scroll down and start answering.
1: In general terms, importance or relevance is called ______.
A. Significance
B. Confidence
C. Freedom
D. Skew
2: Symmetrical distribution of values with the majority of scores “peaking” in the middle is called _____.
A. Normal distribution
B. Degree of freedom
C. Confidence level
D. Standard deviation
3: Skew is the “tail” of a distribution.
A. True
B. False
4: A distribution of values that is flat or low relative to the normal curve is known as _____.
A. Platykurtic
B. Leptokurtic
C. Mesokurtic
D. Platykurtosis
5: A distribution of values that is peaked or high relative to the normal curve.
A. Platykurtic
B. Leptokurtic
C. Mesokurtic
D. Platykurtosis
6: Statistics that estimate the values for a population from a sample of that population is _____.
A. Inferential
B. Descriptive
C. Predictive
D. Factual claim
7: Normal curve is also called _____
A. Bell
B. Dumbbell
C. Spin
D. Skew
8: Curve resulting from the plot of values with a normal distribution is called a normal curve.
A. True
B. False
9: The proposition that the distribution of the average or sum of a large number of samples of a variable will be approximately normal, regardless of the underlying distribution is defined as _____.
A. Central Limit Theorem
B. Law of large numbers
C. Central tendency
D. Confidence intervals
10: A range of values estimated from a sample, within which a value for a population is estimated to fall is called
A. Central Limit Theorem
B. Law of large numbers
C. Central tendency
D. Confidence intervals
11: The distribution of values in a sample is called sampling distribution.
A. True
B. False
12: Statistics used with data assumed to have a normal distribution are called_____.
A. Parametric statistics
B. Sampling deviation
C. Confidence interval
D. Bell curve
13: Statistics used with data that cannot be assumed to have a normal distribution is called
A. Sampling deviation
B. Confidence interval
C. Bell curve
D. Nonparametric statistics
14: A statistical test for determining whether two groups differ significantly in their distribution of scores on the same variable is called
A. Chi-square
B. T-test
C. Anova
D. F value
15: A statistical test for determining whether two groups differ significantly in their distribution of scores on the same variable is called
A. Chi-square
B. T-test
C. Anova
D. F value
16: A statistical test for assessing whether the mean scores for two groups are significantly different is called
A. Chi-square
B. T-test
C. Anova
D. F value
17: The probability that a computed statistic such as a t test or correlation is not due to chance is called _____.
A. Statistical significance
B. Practical significance
C. Effect size
D. Clinical significance
18: Test used when two different groups are being compared is T-test for independent samples.
A. True
B. False
19: A test of the proposition that any difference between two groups will be in one direction is called ______.
A. One tailed
B. Two tailed
C. Three tailed
D. ANOVA
20: A test of the proposition that there will be a difference between two groups but that this difference could be in either direction.
A. Two tailed
B. Three tailed
C. ANOVA
D. None of these
21: Test used when both groups consist of the same people, for example a pretest/posttest comparison.
A. True
B. False
22: ANOVA is written as
A. Analysis of variance
B. T-test
C. Regression
D. Multiple regression
23: ______denotes an analysis of variance value.
A. F-value
B. T-test
C. ANOVA
D. MANOVA
24: The procedure is used when there are multiple dependent variables is called
A. MANOVA
B. ANOVA
C. T-test
D. Chi-square
25: A statistical procedure for measuring the strength of association between two or more variables is called _____.
A. Correlation
B. Regression
C. Causation
D. Covariation
26: Expression of the strength of the relationship between two variables; it ranges between _____and _____ in value. Is known as correlation coefficient.
A. -0.1 to +0.1
B. +0.1 to -0.1
C. -0.2 to +0.2
D. +0.2 to -0.2
27: A statistical method for estimating the strength of relationships among variables is called _____.
A. Regression
B. Correlation
C. Causation
D. Covariance
28: Linear regression assumes that the relationship between variables is____
A. Linear
B. Binary
C. Exponential
D. Non-linear
29: The variable whose value is predicted by the value of ______ variables in a regression analysis is called outcome.
A. Predictor
B. Criterion
C. Response
D. Estimator
30: The variable whose value is predicted by the value of predictor variables in a regression analysis are called _____ variables.
A. Predictor
B. Criterion
C. Response
D. Estimator
31: The variable whose value is predicted by the value of predictor variables in a regression analysis are called predictor values.
A. True
B. False
32: A relationship between two variables that, if plotted out, will show a ____rather than a straight line called curvilinear relationship.
A. Curve
B. Bending
C. Stretching
D. Distortion
33: The use of more than one variable to predict the values for another variable is called ______ regression.
A. Multiple
B. Single
C. Binary
D. None of these
34: Deciding wrongly that there was a significant result when in fact there was not is known as _____.
A. Type I error
B. Type II error
C. Type III error
D. None of above
35: Deciding wrongly that there was no significant result when in fact there was is known as _____
A. Type I error
B. Type II error
C. Type III error
D. None of above
36: Partial correlation and part correlation allow researchers to examine the interaction between a predictor variable and an outcome variable while controlling for ______.
A. Sample size
B. Sampling error
C. Nominal variables
D. The effects of other variables
37: To calculate the probability that a sample has captured the characteristics of a population, we first assume that there is a normal distribution of values in the population.
A. True
B. False
38: Significance is a matter of disciplinary judgment.
A. True
B. False
39: What is the significance of correlation?
A. It predicts the value of one variable, given a value for a related variable.
B. It indicates whether the relationship between two variables is causal.
C. It does not indicate whether the relationship between two variables is causal.
D. It indicates the extent to which two groups differ on one variable.
40: Replication advocates argue that “been there; done that” research is necessary to address the problem of false positives.
A. True
B. False
41: To predict the value of one variable using one other variable, we use ______.
A. Regression
B. Multiple regression
C. Correlation
D. Multiple correlation
42: To predict the value of one variable using two or more predictor variables, we use ______.
A. Regression
B. Multiple regression
C. Correlation
D. Multiple correlation
43: The larger the sample size, the less confidence we can have that the sample statistics reflect population parameters.
A. True
B. False
44: The conventional social science level of significance of 0.05 (95%) is an arbitrary one.
A. True
B. False
45: To compare how three or more groups score on one variable requires which one of the following tests?
A. T test
B. Three-way ANOVA
C. One-way ANOVA
D. Correlation
46: To examine how group membership as a variable interacts with two or more variables we need ______.
A. NOVA
B. ANOVA
C. MANOVA
D. T test
47: Type II error is deciding wrongly that you have no significant result when ______.
A. The null hypothesis is false in the wider population
B. The null hypothesis is true in the wider population
C. Your results have a greater than 5% probability of occurring by chance
D. Your results have a less than 5% probability of occurring by chance
48: What does linear regression do?
A. It predicts the value of one variable, given a value for a related variable.
B. It indicates whether the relationship between two variables is causal.
C. It indicates the strength of the relationship between two variables.
D. It indicates the extent to which two groups differ on one variable.
49: Correlation coefficients indicate what the value of one variable will be given the value of another related variable.
A. True
B. False
50: Path analysis is a technique for mapping causal relationships among variables.
A. True
B. False
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Inferential Statistics MCQs
