Reference no: EM132412575
Assignment -
INSTRUCTIONS - Your final exam will be comprised of 4 separate case studies. For each of these case studies you will be provided a brief overview of the data along with a specific topic of interest (e.g., monitoring the effect of interventions). Each case study has a corresponding dataset that should be used for the analyses and no analysis requires you to combine data across different datasets.
In response to each case study your task is to consider what various analyses can be leveraged to contribute to a more "complete" understanding of the organizational phenomenon (e.g., attrition) in question with the limited data given. The analyses you can choose from are outlined below for your quick reference. Note that while "descriptive statistics" is not an "analysis" per se, I'm including it in the list as a set of analyses you should consider:
- Descriptive Statistics (including frequencies, means, etc.)
- t-test (Independent Samples and/or Paired Samples)
- Chi-square
- ANOVA (One-way and/or Repeated Measures)
- Pearson's Correlation
- Regression (Simple or Multiple Linear Regression)
- Binary Logistic Regression
- Factor Analysis
- Reliability Analysis
You must consider each analysis and indicate whether or not a specific analysis is/would be applicable to the topic of interest. For each case study you will be asked to identify which analyses you will be using simply by indicating it as shown in the table (attached).
The specific analysis selected as well as the number leveraged is your choice and will determine (in part) the score you receive for a given case study. Note that not all of the analyses must be used for a given case study but based on the nature of the data specific analyses will be more appropriate than others (HINT: don't run a logistic regression on a set of data with a continuous DV). Here are some other helpful considerations:
- Descriptive statistics should always be used as an initial analysis to ensure that you understand what kind/amount of data you have.
- Consider each analysis one-by-one before making a decision.
- Remember that each analysis answers a specific question (e.g., significant differences in means vs. likelihood of attrition) so be specific with your wording when articulating what a given analyses is intended to assess.
WHAT YOU MUST SUBMIT - For each analysis that you select, you must articulate (i.e., type out) the following considerations in the template provided to you:
- What analysis are you using and why is this analysis an appropriate selection? (HINT: think characteristics of the data).
- What question is this analysis seeking to answer?
- What did the analysis find / What are the implications? (HINT: be sure that you interpret all applicable statistics - for example, you must interpret the meaning of a beta coefficient in a regression analysis).
Each case study must come with the following:
A completed Case Study template (attached). Each case study template should not exceed two pages (front and back) EXCLUDING the instructions and background provided to you. If it goes over two-pages, it's okay...but consider editing your responses to be more concise. You do not need to include screen shots of your output in the template as you will be providing the output as part of the final submission.
USE CALIBRI 11 POINT FONT TO CONSERVE SPACE.
Syntax for the analyses leveraged in your response.
- There should be a separate syntax file for each case study
- Your syntax should (at minimum) have your name notated in the notes along with a brief note on what analysis is being completed.
- The syntax DOES NOT have to include your interpretation of what you found as that information/content should be completed in the template provided.
Output of the Analysis run. Note that the syntax provided must match the syntax shown in the output.
CASE STUDY 1: EXAMINING EMPLOYEE ATTITUDES
What analysis is being used?
Why is this analysis an appropriate selection?
What question(s) does this analysis seek to answer?
Your response should be specific to the case study - not just the analysis in general.
What did the analysis find / What are the implications?
Be sure to interpret all relevant statistics - and where applicable, the meaning of negative/positive weights/coefficients.
CASE STUDY 2: DIVERSITY ANALYTICS
What analysis is being used?
Why is this analysis an appropriate selection?
What question(s) does this analysis seek to answer?
Your response should be specific to the case study - not just the analysis in general.
What did the analysis find / what are the implications?
Be sure to interpret all relevant statistics - and where applicable, the meaning of negative/positive weights/coefficients.
CASE STUDY 3: SELECTION AND RECRUITMENT
What analysis is being used?
Why is this analysis an appropriate selection?
What question(s) does this analysis seek to answer?
Your response should be specific to the case study - not just the analysis in general.
What did the analysis find / what are the implications?
Be sure to interpret all relevant statistics - and where applicable, the meaning of negative/positive weights/coefficients.
CASE STUDY 4: IMPACT OF HR INTERVENTIONS
What analysis is being used?
Why is this analysis an appropriate selection?
What question(s) does this analysis seek to answer?
Your response should be specific to the case study - not just the analysis in general.
What did the analysis find / What are the implications?
Be sure to interpret all relevant statistics - and where applicable, the meaning of negative/positive weights/coefficients.
Attachment:- Assignment Files.rar