MIM 700 - Data Analytics
Announcements
- Syllabus
- D2L We use the Dropbox to turn in assignments.
Day 1: Introduction to Data Analytics
Successful completion of the MIM degree is far from providing the full skill set for data analytics, but we will provide you with the basics. The reason is the continuing and growing need for Data Analytics in Business.
Introduction to Data Analysis
Sample Data [Excel]
Sample Data [csv]
Homework for Week 1
For any questions about the homework: gerbing@pdx.edu
Turn-in the D2L Dropbox named: Stats_Week_1.
Short-answer questions.
- What is data analytics? How does it fit into the task of management decision making?
- Specify and briefly describe the 4 basic steps of a complete data analysis.
- Describe how data are organize for a data analysis. Why is this organization so amenable to a worksheet program such as Excel?
- In data analysis, what is the concept of degrees of freedom mean?
The following questions apply to the data set analyzed in class: employee data.
- Convert the data to a formal Excel data table and sort by Gender.
- Create the frequency distribution and bar chart for HealthPlan. Interpret.
- Create the frequency distribution and histogram of Years worked at the company. Interpret.
For the following questions, construct your own two small distributions of numerical data, with n=5 (number of data values) in each distribution. Have the distributions represent measurements of an actual business situation.
- Define the type and characteristics of the data entered. Formalize this characterization with data validation. What happens when you enter data out of range?
- Calculate the mean of each distribution manually (as we did in class) and then with the specific Excel function. Interpret each and compare.
- Calculate the standard deviation of each distribution manually (as we did in class) and then with the specific Excel function. Interpret each and compare.
Homework for Week 2
For any questions about the homework: gerbing@pdx.edu
Turn-in the D2L Dropbox named: Stats_Week_1.
Short-answer questions.
- Explain the concept of simulated data.
- What is the reason for computing a confidence interval?
- What is accomplished with a hypothesis test?
For the following questions, simulate the data from a normal distribution of IQ scores, which have a population mean of 100 and a population standard deviation of 15.
- Draw a simulated sample of 8 scores (data values).
- Calculate the sample mean and standard deviation of the 8 scores
- Compare the sample values to their corresponding population values. Do the sample values equal or approximate the corresponding population values? Why?
- Simulate 5 more distributions of 8 scores and calculate the corresponding sample means and sample standard deviations.
- Calculate the standard deviation the sample means (estimated standard error of the mean). How does this standard deviation compare to the standard deviation of the data? Why?
The following questions apply to the first set of 8 simulated IQ scores.
- Calculate the confidence interval of the mean.
- Interpret the confidence interval.
- Does the interval contain the (in this case known) population mean?
- Conduct the hypothesis test against the (in this case known) population mean?
- Interpret the hypothesis test.