Description
The purpose of this assignment is to develop students' abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will learn how statistical analysis is used in predicting an election winner in the first case. In the second case, students will conduct a hypothesis test to decide whether or not a shipping plan will be profitable.
Assignment Steps
Resources: Microsoft Excel®, Case Study Scenarios, SpeedX Payment Times
Develop a 700- to 1,050-word statistical analysis based on the Case Study Scenarios and SpeedX Payment Times.
Include answers to the following:
Case 1: Election Results
- Use 0.10 as the significance level (α).
- Conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state.
Case 2: SpeedX
- Use 0.10 and the significance level (α).
- Conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude the plan will be profitable.
Unformatted Attachment Preview
Purchase answer to see full attachment
Explanation & Answer
find the solution attached
Running Head: ONE-SAMPLE HYPOTHESIS TESTING CASES
One-sample hypothesis testing cases of election results and speedX
(Student name)
(Name of University
1
2
ONE-SAMPLE HYPOTHESIS TESTING CASES
Abstract
This paper carries out a statistical analysis of two case scenarios. The statistical analysis involves
the use of a one-sample hypothesis testing to make a managerial decision. The first case scenario
titled election results, will involve the use of statistical analysis in predicting the election winner.
The second case it will involve conducting a test to decide whether or not a shipping plan will be
profitable.
3
ONE-SAMPLE HYPOTHESIS TESTING CASES
One sample hypothesis test
This is the type of inferential statistic technique that can be used to predict an outcome by
testing the mean. (Insert citation). Hypothesis testing of the mean consists of two hypothesis, the
null hypothesis, referred to as H0, and an alternative hypothesis referred to as H1 or Ha. The null
hypothesis of the one-sample hypothesis of the mean tests whether the population mean is equal
to, less than or equal to, or greater than or equal to a particular constant.
Once the hypothesis is identified, the statistical test statistic is calculated, the value obtained is
compared to what is referred to as the critical Z value which is based on what is called a level of
significance, called α, which is usually equal to 0.10,0.05 or 0.01. Based on this there are two
possible statistical decisions and conclusions that are based on comparing the two Z values. If the
calculated value if Z is greater than the critical value of Z we reject H0. By declining the null
hypothesis, we can conclude we reject H0, Since there is enough statistical evidence to support
H1.On the other hand, if the computed value of Z is less than Z critical then we deduce that there
is no sufficient evidence to support. H1.
The following table summarizes the decisions and conclusion to hypothesis tests in relationship
to the p-value
...