50 interview questions with answers on Parametric Tests

 Here are 50 interview questions with answers on Parametric Tests in Research Methodology, suitable for academic and research interviews:

🔍 Basic Conceptual Questions

1.      What is a parametric test?
A parametric test is a statistical test that makes assumptions about the parameters (mean, variance) of the population distribution from which the sample is drawn.

2.      What are the key assumptions of parametric tests?

o    The data is normally distributed

o    Homogeneity of variances

o    Independence of observations

o    Interval or ratio level of measurement

3.      Name some common parametric tests.

o    t-test (independent, paired)

o    ANOVA (One-way, Two-way)

o    Pearson’s correlation

o    Linear regression

4.      What is the difference between parametric and non-parametric tests?
Parametric tests assume a specific distribution, usually normal, whereas non-parametric tests do not.

5.      When should you use a parametric test?
When the assumptions about normality, equal variances, and measurement level are met.

🧮 T-test Related

6.      What is a t-test?
It is used to determine if there is a significant difference between the means of two groups.

7.      What is an independent samples t-test?
A test comparing the means of two independent groups.

8.      What is a paired samples t-test?
A test comparing the means of the same group at two different times.

9.      What is the formula for the t-statistic in an independent samples t-test?

10.  What is the null hypothesis in a t-test?
There is no significant difference between the means of the two groups.

🧪 ANOVA Related

11.  What is ANOVA?
Analysis of Variance; it compares the means of three or more groups.

12.  What is the null hypothesis in ANOVA?
All group means are equal.

13.  What is F-ratio in ANOVA?
It is the ratio of variance between groups to variance within groups.

14.  What is One-Way ANOVA?
ANOVA with one independent variable having multiple levels.

15.  What is Two-Way ANOVA?
ANOVA with two independent variables, checking interaction effects as well.

16.  What are the assumptions of ANOVA?

·         Normal distribution

·         Homogeneity of variances

·         Independence of observations

17.  What is post-hoc testing in ANOVA?
Follow-up tests (e.g., Tukey’s HSD) done after a significant ANOVA result to find which means differ.

18.  What does a significant F value in ANOVA indicate?
At least one group mean is significantly different.

 Correlation and Regression

19.  What is Pearson’s correlation coefficient?
A measure of linear association between two variables.

20.  What is the range of Pearson’s correlation?
Between -1 and +1.

21.  What does a Pearson’s r of 0 mean?
No linear relationship.

22.  When is Pearson’s correlation used?
When both variables are continuous and normally distributed.

23.  What is simple linear regression?
A model predicting a dependent variable using one independent variable.

24.  What is the equation of a simple linear regression?
Y=a+bX+εY

25.  What does R² represent in regression?
The proportion of variance in the dependent variable explained by the independent variable.

26.  What are the assumptions of linear regression?

·         Linearity

·         Independence

·         Homoscedasticity

·         Normality of residuals

27.  What is multicollinearity?
A situation where independent variables are highly correlated, which affects regression estimates.

28.  How do you check for normality?

·         Histogram

·         Q-Q Plot

·         Shapiro-Wilk test

⚙️ Advanced Concepts

29.  Can parametric tests be used for small samples?
Yes, especially the t-test, but normality should be verified.

30.  What is the Central Limit Theorem’s role in parametric testing?
It justifies the use of parametric tests as sample size increases, normality is approached.

31.  What is homoscedasticity?
Equal variances across groups or levels of an independent variable.

32.  What happens if parametric test assumptions are violated?
The test results may become invalid; non-parametric alternatives should be considered.

33.  What is statistical power in the context of parametric tests?
The probability of correctly rejecting a false null hypothesis.

34.  How do you improve power in a parametric test?

·         Increase sample size

·         Use precise measurement tools

·         Control for confounding variables

35.  What is Type I error?
Rejecting a true null hypothesis.

36.  What is Type II error?
Failing to reject a false null hypothesis.

37.  How are degrees of freedom calculated in a t-test?
df=n1+n2−2df  for independent samples

‍💻 Practical/Software Use

38.  Which software is commonly used for parametric tests?
SPSS, R, Python, SAS, Stata

39.  How do you perform a t-test in SPSS?
Analyze → Compare Means → Independent-Samples T-Test

40.  How do you test normality in SPSS?
Analyze → Descriptive Statistics → Explore → Plots → Normality plots with tests

41.  How do you check for homogeneity of variances?
Levene’s Test is commonly used.

42.  What is the role of p-value in parametric tests?
It indicates the probability that the observed result occurred by chance under the null hypothesis.

 Application-Based Questions

43.  Which test is used to compare pre-test and post-test scores of the same group?
Paired samples t-test.

44.  What test do you use for comparing three teaching methods’ effectiveness?
One-way ANOVA.

45.  What if your data is interval scale but not normally distributed?
Use a non-parametric test like Mann-Whitney U or Wilcoxon signed-rank.

46.  How do you report t-test results in APA format?
t(df) = value, p = value (e.g., t(28) = 2.56, p = .016)

47.  What if you find unequal variances in a t-test?
Use Welch’s t-test.

48.  Which test is used for the strength of relationship between age and income?
Pearson correlation, if both are continuous and normally distributed.

49.  Is Likert scale data suitable for parametric tests?
Debate exists; it’s ordinal, but with 5+ points, it is often treated as interval in practice.

50.  Can ANOVA be used with unequal group sizes?
Yes, but it assumes homogeneity of variances; use Welch ANOVA if this assumption is violated.

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