ethod you are using to compare groups. Copy and paste the output into a Micr
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Part 2
Analyze the data from Part 1 using Microsoft® Excel® software.
Write a 700- to 875-word paper that includes the following information:
- Describe what method you are using to compare groups.
- Copy and paste the output into a Microsoft® Word document, and also answer the following questions:
- What is the significance level of the comparison?
- What was the alpha level you identified in Week 3?
- What was the means and variance for each variable?
- What was the test statistic?
- What was the critical value for both the one- and two-tailed test?
- Was your test one-tailed or two-tailed?
- Were you able to reject the null hypothesis? In other words, did you prove there was a difference?
- Talk about what these results
mean in everyday language and in context to your chosen scenario. - Make a recommendation based on the findings.
Format your paper according to APA guidelines.
Example of Output You Would Use to Answer These Questions
t Test: Two-Sample Assuming Equal Variances |
||
|
Variable 1 |
Variable 2 |
Mean |
4.875 |
8 |
Variance |
5.267857143 |
18.28571429 |
Observations |
8 |
8 |
Pooled variance |
11.77678571 |
|
Hypothesized mean difference |
0 |
|
df |
14 |
|
t stat |
-1.821237697 |
|
P(T <= t) one-tail |
0.045002328 |
|
t Critical one-tail |
1.761310136 |
|
P(T <= t) two-tail |
0.090004655 |
|
t Critical two-tail |
2.144786688 |
|
Step by step
Solved in 3 steps with 3 images
- A study is designed to test the effect of light level on exam performance of high school students. The researcher believes that light levels might have different effects depending on a person's grade in school (1st year, sophomore, junior, or senior), so wants to make sure all grades are equally represented in each treatment. The treatments are fluorescent overhead lighting, yellow overhead lighting, no overhead lighting (only desk lamps). (a) Identify these variables.Imagine you are an educational researcher who wants to learn about the type of psychological atmosphere in which middle school students feel most comfortable and best able to concentrate on their studies. You plan to look at a wide variety of factors that might contribute to such an atmosphere—both physical factors (e.g., cleanliness and colorfulness of the school building) and social factors—(e.g., teacher-student relationships, general tolerance for diverse behaviors and beliefs). You realize that students might identify important factors that you yourself haven't even thought of. In this situation, your best choice would probably be: an experimental study with at least three treatment groups. an experimental study with one treatment group and one control group. a descriptive, quantitative study. a qualitative study.A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What do the results of this study mean to you?
- A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is the null hypothesis?A two-factor study investigates the effects of self-esteem (low vs. high) and gender (males vs. females) on anxiety scores. The following data represents the means for each treatment condition. Low self-esteem High self-esteem Male 5 12 Female 10 3 The data shows that there is a self-esteem by gender interaction. a. Explain the self-esteem by gender interaction (include individual means in your explanation)A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. Is there significance for either gender or income?
- A researcher wants to see if gender and/or income affect the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affect the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables affected total help if he rejects the null hypothesis. What is one research hypothesis (there are three possible hypotheses here name them all if you can but naming at least one is required)?If there is an interaction between the variables of “activity level” and “time of day,” this means that activity level does not have the same effect at different times of day. Group of answer choices True FalseA psychologist conducted a survey of the attitude towards the sustainability of American energy consumption with 250250 randomly selected individuals several years ago. The psychologist believes that these attitudes have changed over time. To test this he randomly selects 250250 individuals and asks them the same questions. Can the psychologist confirm his theory that the attitudes have changed from the first survey to the second survey? Attitude 1st Survey 2nd Survey Optimistic 50%50% 52%52% Slightly Optimistic 16%16% 10%10% Slightly Pessimistic 11%11% 15%15% Pessimistic 23%23% 23%23% Copy Data Step 6 of 10 : Find the value of the test statistic. Round your answer to three decimal places. Step 7 of 10: Find the degrees of freedom associated with the test statistic for this problem Step 8 of 10: Find the critical value of the test at the 0.025 level of significance. Round your answer to three decimal places.step 9 of 10: make the decision to reject or fail to reject…
- Based on a graph below which of the following statement describes the best types of associations between Factors A, C, and D and the Disease: (choose one best answer) Factor Factor C Disease Factor A O Factor A is sufficient but not necessary, while Factors C and D and neither sufficient not necessary. O Factors A, C and D are neither sufficient nor necessary. O Factor A is necessary but not sufficient, while Factors C and D are necessary but not sufficient. O Factor A is sufficient but not necessary, while Factors C and D are neither sufficient not necessary.How forecasting is quite different from the estimation of causal effects.?In a theoretical study, it was found that insomnia is associated with depression. It was also pointed out that stress could cause a person to have insomnia which is also related to having depression. The relationship between stress and insomnia is said to be: Bidirectional Indirectly causal Directly causal Noncausal Answer