### PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests

## PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests

Name

Capella University

PSYC FPX 4700 Statistics for the Behavioral Sciences

Prof. Name

Date

**Hypothesis, Effect Size, Power, and t Tests**

**Problem Set 3.1: Sampling Distribution of the Mean Exercise**

**Criterion: Interpret population mean and variance.**

Suppose a researcher wants to learn more about the mean attention span of individuals in some hypothetical population. The researcher cites that the attention span (the time in minutes attending to some task) in this population is normally distributed with the following characteristics: μ = 20, σ^2 = 36.

- What is the population mean (μ)? 20
- What is the population variance (σ^2)? 36
- Sketch the distribution of this population. Make sure you draw the shape of the distribution and label the mean plus and minus three standard deviations.

**Problem Set 3.2: Effect Size and Power**

**Criterion: Explain effect size and power.**

Two researchers make a test concerning the effectiveness of a drug use treatment. Researcher A determines that the effect size in the population of males is d = 0.36; Researcher B determines that the effect size in the population of females is d = 0.20. All other things being equal, which researcher has more power to detect an effect? Explain.

Two researchers make a test concerning the levels of marital satisfaction among military families. Researcher A collects a sample of 22 married couples (n = 22); Researcher B collects a sample of 40 married couples (n = 40). All other things being equal, which researcher has more power to detect an effect? Explain.

### PSYC FPX 4700 Assessment 3 Hypothesis Effect Size Power and Tests

Two researchers make a test concerning standardized exam performance among senior high school students in one of two local communities. Researcher A tests performance from the population in the northern community, where the standard deviation of test scores is σ = 110; Researcher B tests performance from the population in the southern community, where the standard deviation of test scores is σ = 60. All other things being equal, which researcher has more power to detect an effect? Explain.

**Problem Set 3.3: Hypothesis, Direction, and Population Mean**

**Criterion: Explain the relationship between hypothesis, tests, and population mean.**

Directional versus nondirectional hypothesis testing. Cho and Abe (2013) provided a commentary on the appropriate use of one-tailed and two-tailed tests in behavioral research. In their discussion, they outlined the following hypothetical null and alternative hypotheses to test a research hypothesis that males self-disclose more than females:

H0: µmales – µfemales ≤ 0 H1: µmales – µfemales > 0

- What type of test is set up with these hypotheses, a directional test or a nondirectional test?
- Do these hypotheses encompass all possibilities for the population mean?

**Problem Set 3.4: Hypothesis, Direction, and Population Mean**

**Criterion: Explain decisions for p values.**

The value of a p value. In a critical commentary on the use of significance testing, Lambdin (2012) explained, “If a p < .05 result is ‘significant,’ then a p = .067 result is not ‘marginally significant’” (p. 76).

Explain what the author is referring to in terms of the two decisions that a researcher can make.

**t-Tests**

**Problem Set 3.5: One-Sample t test in JASP**

**Criterion: Calculate a one-sample t test in JASP.**

Data: Use the dataset minutesreading.jasp. The dataset minutesreading.jasp is a sample of the reading times of Riverbend City online news readers (in minutes). Riverbend City online news advertises that it is read longer than the national news. The mean for national news is 8 minutes per week.

Instructions: Complete the steps below.

- State the nondirectional hypothesis.
- State the critical t for a = .05 (two tails).
- Is the length of viewing for Riverbend City online news significantly different than the population mean? Explain.

**Problem Set 3.6: Confidence Intervals**

**Criterion: Calculate confidence intervals using JASP.**

Data: Continue to use the dataset minutesreading.jasp.

Instructions: Based on the output from Problem Set 6.2, including a test value (population mean) of 8, calculate the 95% confidence interval by following the steps below.

**Problem Set 3.7: Independent Samples t Test**

**Criterion: Calculate an independent samples t test in JASP.**

Data: Use the dataset scores.jasp. Dr. Z is interested in discovering if there is a difference in depression scores between those who do not watch or read the news and those who continue with therapy as normal. She divides her clients with depression into 2 groups. She asks Group 1 not to watch or read any news for two weeks while in therapy and asks Group 2 to continue with therapy as normal. The dataset scores.jasp is a record of the results of the measure, administered after 2 weeks.

Instructions: Complete the steps below.

**Problem Set 3.8: Independent t Test in JASP**

**Criterion: Identify IV, DV, and hypotheses and evaluate the null hypothesis for an independent samples t test.**

Data: Use the information from Problem Set 3.7.

Instructions: Complete the following:

- Identify the IV and DV in the study.
- State the null hypothesis and the directional (one-tailed) alternative hypothesis.
- Can you reject the null hypothesis at α = .05? Explain why or why not.

**Problem Set 3.9: Independent t Test using Excel**

**Criterion: Calculate an independent samples t test in Excel.**

Data: Use this data:

Depression Scores:

Group 1: 34, 25, 4, 64, 14, 49, 54

Group 2: 24, 78, 59, 68, 84, 79, 57

Instructions: Complete the following steps:

- Open Excel.
- On an empty tab, enter the data from above. Use column A for group 1 and column B for Group 2. In Cell A1, enter 1. In cell B1, enter 2.
- Enter the data for each group below the label.
- Click Data Analysis, select t-Test: Two-Sample Assuming Equal Variances. Click OK.
- Copy the results from both t tests below.

**References:**

Cho, S., & Abe, S. (2013). [Title of the paper]. Journal Name, Volume(Issue), page numbers.

Lambdin, C. (2012). [Title of the paper]. Journal Name, Volume(Issue), page numbers.