Hypothesis Testing & t-Value

Calculate the degrees of freedom for a sample size of 25.

• 26

• 24

• 25

• 23

Determine the critical t-value for a two-tailed test with a significance level of 0.05 if n=5.

• ±2.776

• ±1.96

• ±3.291

• ±1.645

Identify the t-value with a significance level of 0.01 and n=23.

• 2.508

• 2.500

• 1.321

• 1.319

Describe how to determine the t-value from the t-table.

• Use the sum of the row and column values in the t-table to find the t-value.

• Check the row for the desired confidence level and the column for degrees of freedom in the t-table.

• Locate the intersection of the row for degrees of freedom (df) and the column for the desired confidence level in the t-table.

• Calculate the average of the row and column values in the t-table.

Define the significance level in the context of hypothesis testing.

• The significance level in hypothesis testing is the probability of rejecting the null hypothesis when it is actually true.

• The significance level is the confidence level in the alternative hypothesis.

• The significance level is the probability of accepting the null hypothesis when it is actually false.

This type of distribution is used instead of the normal distribution when you have small samples (n<30).

• Frequency distribution

• Semi-normal distribution

• t-distribution

• z-distribution

  
  

Differentiate between one-tailed and two-tailed tests in hypothesis testing.

• One-tailed tests have higher statistical power than two-tailed tests.

• One-tailed tests focus on one specific direction of the effect, while two-tailed tests consider both sides of the distribution.

• One-tailed tests focus on two specific directions of the effect, while two-tailed tests consider only one side of the distribution.

• One-tailed tests are used for qualitative data, while two-tailed tests are used for quantitative data.

Find the t-value whose degree of freedom is 14 and has 𝛼 = 0.001

• 2.650

• 3.733

• 3.787

• 3.852

Determine the sample size for a degree of freedom of 33.

• 32

• 35

• 36

• 34

This is a proposed explanation, assertion, assumption, or claim about a population parameter or about the distribution of a random variable.

• A.      Conclusion

• B.      Explanation

• C.      Hypothesis

• D.      Theory