Ketty work:
You must use the Sample Report file to format the papers. You must use the Examples Report below to format the results.
You must use the Assignment grading criteria to fully answer all questions.
Read the following hypotheses:
· Confidence in recall differs depending on the level of stress.
· Recall for participants in high-stress conditions will deteriorate over time.
· Boys will have higher levels of confidence than girls.
In a 1- to 2-page Microsoft Word document, for each hypothesis listed above, indicate:
· Describe how a Type I error might occur, given the context of the assignment. Describe how a Type II error might occur,given the context of the assignment
· Whether the appropriate analysis would be a one-tailed test or a two-tailed test
Submission Details:
· Name your document SU_PSY2008_W5_A2_LastName_FirstInitial.doc.
· Submit your document to the W5 Assignment 2 Dropbox by Week 5, Day 6.
Assignment Grading Criteria |
Maximum Points |
Explained whether each hypothesis is a one-tailed test or a two-tailed test. |
5 |
Correctly identified the type I error for each hypothesis. |
5 |
Correctly identified the type II error for each hypothesis. |
5 |
Used correct spelling, grammar, and professional vocabulary. Used APA format. |
5 |
Total: |
20 |
Example report
W5A2 |
H1: ___ tailed H2: ___ tailed H3: ___ tailed
Type I error for: H1 = H2 = H3 =
Type II error for: H1 = H2 = H3 = |
EXAMPLES
The results in your assignments must be stated following the examples provided in the classroom, as follows:
W1A2 |
Subject (ID) – Alphanumeric – Use two numbers for all IDs. No letters.
Age – Numeric – Use two numbers only. No letters.
Sex – Alphanumeric – Uses one letter only: M=male or F=female.
Height - Numeric - This must be only two numbers: the total height in inches only.
Year in college – Alphanumeric – Forty students who are five males and five females in each year of college. Use one letter only: F=freshman, S=sophomore, J=junior, and S=senior. (You must choose a different letter to show the difference between sophomores and seniors, it is your decision how to show this difference)
|
W2A1 |
EXAMPLE: There were seventy-two participants recruited from an introductory psychology class at South University. There were x males and x females, with x Caucasian, x African Americans, and x other ethnicities represented. The ages ranged from x to x years, with a mean age of x years, SD x. Each participant watched a movie and rated his or her satisfaction on a scale of 1 to 10. The mean level of satisfaction was x, SD x. |
W2A2 |
EXAMPLE: There were seventy-two participants recruited from an introductory psychology class at South University. There were thirty-six males and thirty-six females, with twenty-four Caucasian, twenty-four African Americans, and twenty-four other ethnicities represented. The ages ranged from x to x years, with a mean age of x years, SD x. Each participant watched a movie and rated his or her satisfaction on a scale of 1 to 10. The mean level of satisfaction was x, SD x. |
W3A1 |
Age Results The top 5% (z-score above 1.645) Subject Id: _____
Bottom 5% (z-score below -1.645) Subject Id: _____
Top 2.5% (z-score above 1.96) Subject Id: ____
Bottom 2.5% (z-score below -1.96) Subject Id: ____
Height Results
Top 5% (z-score above 1.645) Subject Id: ____
Bottom 5% (z-score below -1.645) Subject Id: _____
Top 2.5% (z-score above 1.96) Subject Id: ____
Bottom 2.5% (z-score below -1.96) Subject Id: _____ |
W3A2 |
||||||||||||||||||
Q#2
Extremely high score = z score of ___ above the mean = participant #___ scored ___
Extremely low score = z score of ___ below the mean = participant #___ scored ___
Q#3
|
W5A1 |
Between groups design:
DV =
IV = Level 1 = Level 2 =
Within subjects design:
DV =
IV = diet Level 1 =
IV = Level 1 = Level 2 = |
W5A2 |
H1: ___ tailed H2: ___ tailed H3: ___ tailed
Type I error for: H1 = H2 = H3 =
Type II error for: H1 = H2 = H3 = |
W6A1 |
EXAMPLE: A one-sample t-test was conducted to find whether age in the sample was different from age in the general population. The t-test (was/was not) significant; t(x)= x, p = x; participants in the sample (M = x, SD = x) were significantly (more/not more) than the general population (M = x). The null hypothesis (is/is not) rejected.
ALSO MUST INCLUDE: If the t statistic is in the rejection region, reject the null hypothesis. OR If the t statistic is not in the rejection region, accept the null hypothesis. |
W6A2 |
EXAMPLE: A one-sample t-test was conducted to find whether the overall stress of participants in the eyewitness experiment was different from that of the general population of students in online universities. The t-test (was/was not) significant; t(x)= x, p = x; participants in the eyewitness experiment (M = x, SD = x) (were/were not) significantly more stressed than the general population of students in online universities (M = x). The null hypothesis (is/is not) rejected.
ALSO MUST INCLUDE: If the t statistic is in the rejection region, reject the null hypothesis. OR If the t statistic is not in the rejection region, accept the null hypothesis. |
W7A1 |
EXAMPLE: An independent-samples t-test was run to determine whether there were differences in height between men and women. The test (was/was not) significant (t(x) = -x, p = x). Men (M = x, SD = x) (do/do not) differ from women (M = x, SD = x) in height.
ALSO MUST INCLUDE: If the t statistic is in the rejection region, reject the null hypothesis. OR If the t statistic is not in the rejection region, accept the null hypothesis.
|
W7A2 |
ALSO MUST INCLUDE: Was the null accepted or rejected? What does this mean to the results of the analysis? Explain.
EXAMPLES:
Independent Samples: An independent-samples t-test was run to determine whether there were differences in satisfaction between men and women. The test (was / was not) significant (t(x) = -x, p = x). Men (M = x, SD = x) (do / do not) differ from women (M = x, SD = x) in their levels of satisfaction. Paired Samples: The participants were tested immediately after they viewed the movie and again one week later to see whether their satisfaction with the movie changed significantly. A paired-samples t-test was run, and it was found that the scores (did / did not) change significantly (t(x) = x, p = x). The mean satisfaction score immediately following the movie was x, SD = x. One week later, the satisfaction significantly (increased / not increased) with mean x, SD = x. The null hypothesis is (accepted/rejected) because... |
W8A1 |
EXAMPLE: A simple ANOVA was run to test the hypothesis that there are significant age differences across years in college. The results indicated that a significant difference (does / does not) exist, with F(x) = x, p = x. Post hoc tests using the Tukey method indicated that the age of freshmen (M = x) (were / were not) significantly lower than the age of seniors (M = x). The ages of sophomores (M = x) and juniors (M = x) (were / were not) significantly different from either freshman or seniors.
ALSO MUST INCLUDE: The interpretation of the results – what do the results tell us about the hypothesis of age differences across years in college? What do the results mean? |
W8A2 |
EXAMPLE: A simple ANOVA was run to test the hypothesis that there would be differences in satisfaction levels depending on the type of movie participants viewed. The results indicated that a significant difference (does / does not) exist, with F(x) = x, p = x. Post hoc tests using the Tukey method indicated that the satisfaction with comedies (M = x) (was / was not) significantly higher than the satisfaction with action movies (M = x). Romantic comedies (M = x) (were / were not) rated differently from either comedies or action movies.
ALSO MUST INCLUDE: The interpretation of the results – what do the results tell us about recall? About stress levels? About the relationship between the two? What do the results mean? |
W9A1 and W9A2 |
ALSO MUST INCLUDE: Discuss the nature of the correlation when writing the results. Do not just state if there is a correlation or not. Explain what the correlation coefficient means. What do the results tell us about the relationship between the variables? EXAMPLE for no correlation To determine if a relationship exists between the age at which a movie is viewed and the satisfaction rating for that movie, a correlation was run and it was found there was no significant relationship between these two variables (r = x, p = x). EXAMPLE for negative correlation To determine if a relationship exists between the age at which a movie is viewed and the satisfaction rating for that movie, a correlation was run and it was found that there was a significant negative correlation (r = -x, p= x). As age increases, satisfaction decreases. EXAMPLE for positive correlation To determine if a relationship exists between the age at which a movie is viewed and the satisfaction rating for that movie, a correlation was run and it was found that there was a significant positive correlation (r = -x, p= x). As age increases, satisfaction increases.
|
W10A1 and W10A2 |
EXAMPLE: Researchers were interested in determining whether a relationship exists between owning a home and owning a pet. A chi-square analysis was conducted, which returned x (x) = x, p = x suggesting that there is/is not a significant relationship between the two variables. Looking at the data , for those who own homes, x out of x people also own pets. On the other hand, for those who do not own their homes, only x out of x people own pets.
ALSO MUST INCLUDE: Discuss the nature of the results. Do not just state the results. Explain what the results mean. What do the results tell us about these variables and their relationship? |

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