5 Stats - Inferential Statistics

What is the purpose of inferential statistical tests?

• To describe the data collected from a sample.

• To analyze the variability within a sample dataset.

• To determine the correlation between variables.

• To make inferences about a population from a sample of that population.

What are the two key concepts in inferential statistics?

• Standard error and confidence intervals.

• Null hypothesis and sampling distributions.

• P-values and null hypothesis significance testing (NHST).

• Variance and effect sizes.

Who introduced the concept of p-values?

• Karl Pearson.

• Ronald Fisher.

• Francis Galton.

• Charles Spearman.

What does a p-value illustrate?

• The variability in sample data.

• The probability that the null hypothesis is true.

• How well sample data support the view that the null hypothesis is true.

• The range of potential outcomes in a dataset.

What does the null hypothesis represent?

• The presence of a significant effect.

• A state of no effect or no difference.

• The expected variability within a dataset.

• The assumption of a directional relationship.

What is the main idea behind null hypothesis significance testing (NHST)?

• To test if a sample mean equals the population mean.

• To assume no effect until evidence demonstrates otherwise.

• To compare confidence intervals between groups.

• To analyze variability within the data distribution.

Why does science adopt a skeptical starting point like the null hypothesis?

• Because evidence-based conclusions are often subjective.

• To ensure the validity of alternative hypotheses.

• Because the philosophical basis of science is skepticism, requiring evidence to support claims.

• To avoid Type 2 errors in statistical testing.

What does a high p-value indicate?

• That the null hypothesis is rejected.

• That the observations are likely assuming the null hypothesis is true.

• That the sample size is too small.

• That the data are inconsistent with the null hypothesis.

What does a low p-value indicate?

• That the null hypothesis is likely to be true.

• That the variability in the data is minimal.

• That the observations are unlikely assuming the null hypothesis is true.

• That the sample data support the null hypothesis.

What is the conventional cut-off p-value for statistical significance in psychology?

• 0.10.

• 0.01.

• 0.001.

• 0.05.