Statistics and Hypothesis Testing

What does a negative skew indicate?

• Most values are concentrated on the left with a tail on the right

• Most values are concentrated on the right with a tail on the left

• A perfectly symmetrical distribution

• A uniform distribution

What is the significance level commonly used in hypothesis testing?

• 0.01

• 0.05

• 0.10

• 1.00

The null hypothesis (H₀) states that:

• There is a significant effect

• There is no effect or difference

• The sample is biased

• The hypothesis cannot be tested

What is a key assumption of an independent t-test?

• The data must be non-normally distributed

• The groups must be related

• The variances must be equal

• The sample size must be at least 100

What is the primary purpose of inferential statistics?

• To describe the data collected

• To make predictions or generalizations about a population

• To create graphs and visualizations

• To summarize the central tendency

What does a confidence interval of 95% indicate?

• There is a 95% probability that the population mean falls within the interval

• 95% of the sample data fall within the interval

• The sample mean is exactly 95% accurate

• There is a 5% probability that the results are incorrect

If the F-statistic is larger than the critical F-value in ANOVA, you should:

• Reject the null hypothesis

• Fail to reject the null hypothesis

• Increase the sample size

• Use a t-test instead

True or False: ANOVA can compare more than two groups.

• True

• False

What does a high standard deviation indicate?

• Data points are close to the mean

• Data points are widely spread out

• The dataset contains only positive values

• The dataset is normally distributed

What does Cohen’s d measure?

• The variance of a dataset

• The effect size between two means

• The correlation between two variables 

• The probability of Type I error