A+ paper | Economics homework help
Please answer the following question thoroughly, addressing every one of the questions asked. Then, respond to your classmates’ answers to the question. Remember that your requirement is to post at least eight times totally over at least three separate days.
Descriptive Statistics
Read the research scenario and then answer the questions based on what you have learned in Chapter 12.
Scenario:
An industrial organizational psychologist is in charge of evaluating the effect of employee training procedures aimed at increasing the efficiency of processing client inquiries at an international company. This company receives many inquiries about its products and services over the telephone, via e-mail, and through regular mail. There is a multi-step process for handling these inquiries, the details of which need not concern us. Twenty employees are identified and randomly assigned in equal numbers (n = 10) to two different training conditions (A and B). The dependent measure is number of inquiries processed correctly by each employee in a 72-hour work period following the week-long training. Data are collected from all 20 participants.
What statistical procedure is recommended first?
What descriptive statistics should the researcher obtain in order to summarize the data?
What is the researcher looking for when the two means are obtained?
What is a recommended measure of effect size in this situation?
Assume the researcher found that Cohen’s d was .88. What might be concluded?
To help confirm what the data are showing, the researcher seeks evidence for how well the difference between the sample means in the two training conditions represents the true difference between the population means. What might be recommended at this point?
The researcher finds that the .95 confidence interval for the difference between independent means contains zero. What should the researcher conclude?
Week 5 DQ 2
Please answer the following question thoroughly, addressing every one of the questions asked. Then, respond to your classmates’ answers to the question. Remember that your requirement is to post at least eight times totally over at least three separate days.
Analyses of Variance Research
Reading ANOVA Summary Tables
An analysis of variance (ANOVA) is typically carried out using a statistical software package. Learning to “read” the computer output is extremely important. Look over the ANOVA summary tables below and attempt to answer the questions that follow.
Results of a single-factor independent groups design are as follows:
|
Source |
Sum of Squares |
df |
Mean Square |
F |
p |
|
Factor A |
420.00 |
3 |
140.00 |
28.00 |
0.000 |
|
Error |
780.40 |
156 |
5.00 |
||
How many levels of Factor A are there?
What is the total number of subjects in the experiment?
Assuming an equal number of subjects in each group, what is the group size?
Are the results of the omnibus F-test statistically significant?
(a) What does the researcher know on the basis of these results?
(b) What does the researcher not know?
Applied Research Questions
Objectives:
Prepare written responses to the following questions. The response to each bulleted question should be at least 250 words in length.
What are the similarities between descriptive and inferential statistics? What are the differences? When should you use descriptive and inferential statistics?
What are the similarities between single case studies and small-N research designs? What are the differences? When should you use single case studies and when should you use small-N research designs?
What are true experiments? How are threats to internal validity controlled by true experiments? How are they different from experimental designs?
What are quasi-experimental designs? Why are they important? How are they different from experimental designs?
What type of data collection do you think would be most appropriate for your experimental method? How do you think you should statistically analyze this data? Will you compare means? Find a correlation? Remember to describe both descriptive and inferential statistics.
