- Description
QNT 275 Week 5 Practice: Week 5 Discussion
Review the Discussion FAQs Module.
Reference the Week 4 Case Study.
Respond to one of the following:
- Regarding requirement #2: What impacted the reps’ average weekly performance to be greater than the population mean?
- Regarding requirement #3: Considering your hypothesis statements, provide an example of a Type I and a Type II error.
- Regarding requirement #3: Considering the p-values, is a statistically significant difference between the two reps being considered for the manager’s position? Explain.
- Regarding requirement #3: Who would you recommend being promoted to Sales Manager: Rep A or Rep B? Why?
- Regarding requirement #4: Considering the outcome of the hypothesis test, is your new Sales Manager outperforming the sales force?
Time Series
Time flies! We are at the last week of the course! I wanted to take my chance to push in some discussions on time series, a special type of data that are collected over a course of time. We build model based on these data for predictions through observing different components: trend, cycle, seasonal, irregular. Here are some applications of time series data forecasting/prediction in the real world:
Sales forecasting
1) Declining sales
2) Seasonal peaks and valleys
Staffing requirements
1) Absenteeism
2) Contract or permanent employee
Budgeting
1) Revenue or expenditures over time
2) Annual appropriations for government agencies
Potential global market expansion
1) Sales force estimation
2) Potential market demand
Material requirements
1) Cost of goods sold
2) Matching production schedules with raw material requirements
Please chime in and share what you learned!
Choosing the right test
Hi Class,
It’s impossible for us to understand the variety of statistical tests that you are newly exposed in one week or even 5 weeks – one is enough to make our heads spinning 🙂 I would like to, however, share with you some articles about choosing the appropriate hypothesis test in a bigger picture. Here is the link http://www.diss-stat.com/choosing.pdf
The choice of statistical test depends on the research goal/question and the nature of the data collected. If we would like to find the association between two variables, we would calculate the correlation. If our goal is to compare the means between two groups, we use a T or Z test. If we want to compare two proportions, then we also perform a z-test. If we want to compare the means across multiple groups (more than 2), we use ANOVA test.
I do not expect that you understand them all, rather to give you an idea of it. Cheers!