Qnt 351 entire course

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QNT 351 Entire Course QNT 351 Week 1 Complete DQs (1) How would you define statistics? How is statistics used in business decision making? (2) What is the importance of statistics in business decision making? Describe a business situation where statistics was used in making a decision. (3) How do we define measurement? What are various levels of measurement? How do you select measurement levels when developing a survey or data collection tool? Explain with examples. QNT 351 Week 1 Individual Statistics in Business QNT 351 Week 2 Complete DQs (1) Describe a business situation, other than what has already been selected by fellow students or selected from the team assignment, where mean and standard deviation can be used in decision making. Describe how calculation of mean and standard deviation can help in making a decision. (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? (3) Select an article from a news magazine or research journal where data is displayed in a pie or bar chart. Describe the data displayed in the chart and what conclusion you could draw. QNT 351 Week 2 Team Data Collection paper QNT 351 Week 2 Team Data Collection Presentation QNT 351 Week 3 Complete DQs (1) What are the differences between probability and coincidence? Can the probability be more than 1 or less than 0? Explain why or why not. (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. (3) What are some conditions under which business decisions are made using subjective probability concepts? Provide at least two examples of subjective probability. QNT 351 Week 3 Team Summarizing and Presenting Data QNT 351 Week 4 Complete DQs


(1) What are the five steps in the hypothesis testing procedure? Are the steps followed in sequence? Explain why or why not. How does the five-step procedure for hypothesis testing differ when comparing two groups using a t- or z-test? How is the process similar? (2) What is the importance of a 5% significance level? Why would you choose 5% as opposed to 10% or 1%? What effect does the level of significance have on a Type II error? (3) Why is the coefficient of correlation an important tool for statisticians? Provide some specific examples from real life. QNT 351 Week 4 Team Reflection QNT 351 WEEK 5 QNT 351 Week 5 Team Analyzing and Interpreting Data paper QNT 351 Week 5 Team Analyzing and Interpreting Data Presentation


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