QNT 351 Weeks 1-5 All DQs

Week 1, DQ 1

What is the importance of statistics in business decision making? Describe a business situation where statistics was used in making a decision.

Week 1, DQ 2

How would you define a variable? What is the difference between a dependent and independent variable? Do you think both variables are used in every research? Explain why or why not. Provide examples.

Week 1, DQ 3

Select four variables, other than what your fellow students have already selected, that could be measured by nominal, ordinal, interval, and ratio scale. Classify them by measurement scale and select descriptive statistics that can be used to summarize data. Use the following table when posting your response:

Level of Measurement

Descriptive Stat and Justify Selection  Nominal Ordinal  Interval Ratio

Week 2, DQ 1

What are the various methods one can use to identify the shape of data distribution collected for research study? Why it is important to know the shape of distribution? How it can be used in decision making? Provide examples other than those already posted in class.

Week 2, DQ 2

Can mean, median, or mode be calculated from all statistical data? Explain why or why not. When is the mean the best measure of central tendency? When is the median the best measure of central tendency?

Week 2, DQ 3

Select an article from a news magazine or research journal where data is displayed in a graph. Describe the data displayed in the graph and what conclusion you could draw.  Be sure to include a reference to the article that you used.

Week 3, DQ 1

An oil change shop advertised to change oil within 15 minutes. Based on the data collected on a typical day, what is the probability that oil change will take 15 minutes or less time? Based on the data, do you think the business claim is valid? Explain why or why not.

Times(minutes):  6, 7.5, 9, 11, 11, 11.5, 12, 12.5, 13, 14, 15, 16, 17, 17, 17.5, 18.5, 20.5, 22, 24, 29

Week 3, DQ 2

What are the characteristics of standard normal distribution? The HR department of an organization collects data on employees’ age, salary, level of education, gender, and ethnicity. Which data do you think is more likely to follow normal distribution? Explain why.

Week 3, DQ 3

How would you calculate area between two data values? How would you calculate area above or below a certain value? How can knowing these areas help you?

Week 4, DQ 1

What is the five-step process for hypothesis testing? Is the order important? Explain why or why not. Why do alphas differ among industries? How do ethics affect your chosen level of significance? Can you reject and accept the null hypothesis at the same time? Explain why or why not.

Week 4, DQ 2

Why does the significance level differ among industries? Will the null hypothesis be more likely to be rejected at α = 0.01 than α = 0.10? As the significance level increases to α = 0.10 from α = 0.01, which type error is more likely to occur? What can be done to reduce the likelihood of incurring this error?

Week 4, DQ 3

Why is the coefficient of correlation an important tool for statisticians? Provide some specific examples from real life.

Week 5, DQ 1

How would you select appropriate statistical tests for analysis research data? What aspects of research questions or data types are relevant considerations in choosing your tests? Why?

Week 5, DQ 2

How do you know you have validated a research study based on data gathered from primary or secondary sources? Have you been involved with any product test-marketing project? Explain. How did the resulting statistics affect the product’s marketing strategy? How can organizations skew the statistical outcomes of their business research?

Week 5, DQ 3

In what way has the learning from this course helped you to effectively test hypotheses, draw conclusions, and provide recommendations to management? Consider what you have achieved in your research study conducted for this course.