A large number of pupils in her school have taken the exam and in order to save time she decides to take a random sample of her pupils' results. For example, the average GCSE English results of the schoolchildren is higher than the national average a one-tailed hypothesis , or the average GCSE English results of the schoolchildren is different from the national average a two-tailed hypothesis. Next, calculate the test statistic, using the formula above in the red box.
Compare the test statistic to the critical values. Form conclusions. Otherwise you accept it. Double click on Shift. Choose Assume equal variances and OK. H 0 is accepted, shift defects are the same. It is similar to problems done earlier. Others should create a worksheet containing both a data variable and a source variable using procedures discussed earlier.
Do not assume equal variances. Problem II message: This is a paired difference test. Those using Quick's data files should load Mini Others should add 3 variables to their page worksheet, one for the efficiency before training, one for the efficiency after training, and one to store the difference.
Be sure to match each employee with their before and after efficiency rating. Choose Calc and Calculator. Use Select to copy Difference into the Store results in variable. Highlight Before and use Select to copy it into the Expression box. Choose the calculator subtraction sign. Highlight After and use Select to copy it into the Expression box.
Choose Stat, Basic Statistics, and 1 Sample t. Double click on Difference. Choose Test mean and leave it at 0. Set Alternative Hypothesis to less than and choose OK.
Training increased efficiency. Others should create a page worksheet with a 36 row variable named Weight and a source variable named Sample Number. Each sample number will be entered 3 times. Double click on Weight to copy it into the Single column and double click on Sample Number to copy it into Subgroup size. See page PS for the answer. Actual data is needed. Chapter 18 on Analysis of Variance Problem I message: This two-sample analysis of the variance should be done by hand.
Others should create a 2 variables worksheet for page One variable is for Weight data and one for Department. Copy Weight into Response with a double click. Copy Department into Factor with a double click. Part mean weights are not equal. Those using Quick's worksheet should load Mini Others should create a 3 variable file containing data on Weight, Department, and Time. When doing time, be sure to match each time with the appropriate department and weight.
Problem II message: This problem emphasizes the concept of statistical independence. Those using Quick's data worksheets should load Mini Others should create a 2 variable worksheet to store the data presented in the problem table. The first variable entitled Younger contains 24 and The second entitled Older contains 12 and 8. Chi square is zero and H0 is accepted. Making a sale and age are independent.
Problem data was first presented on page Others should load their page 68 data file. Double click on Weight. Check the bull's eye next to Above and below and insert the median of Problem II message: This is a one sample sign test of the median. Others should create a one variable worksheet for the page median data. Double click on Median. Check the bull's eye next to Test median and insert the median of 5.
Set Alternative hypothesis to greater than and choose OK. The median has not increased. Problem III This is a two sample medians test.
Others should create a data file with 2 variables, one for sick days taken by graduates and the other for sick days of non-graduates. Double click on Graduates and then Non-graduates. Set Alternative to not equal and choose OK.
Reject H0 as. Median sick days differ. Note: z of 3. Others should add 2 variables to their page worksheet, one for Median Weight listed by departments and a second for Departments The outcome shows the P-value was 0. The Graphs We must take a look of the graph, before we check the box of " Assuming equal variances". It would give us evidence whether the variances are close or not. In this example, we didn't assume two populations have same variance.
Unless we check " Assuming equal variances" box, Minitab would not assume that the population have equal variances, so the test statistic is , with degree of freedom.A lower bound means that is the smallest the values can be, but it could be more. Those using Quick's worksheets should load worksheet Mini To address this question, we can carry out two-sample t test. Set Alternative Hypothesis to less than and choose OK. Paired T: Use this when you're using two dependent. Note: the problem's sigma of. Options Each hypothesis test has an Options button.
Double click on Mini Note: the problem's sigma of. When working with proportions in this class, there are check boxes under Options that should be selected.
The distribution being used. Load the page 6 data by double clicking on Mini Each sample number will be entered 3 times. See page PS for the answer.
You want each value listed once and the entire sequence listed once Randomly Selecting the Dates Label a column as picked. For question 5c, try using Cumulative probability. Others should create a data file with 2 variables.
Insert all the parameters from question 1 a-d into the question 1 data column. Choose the Test Mean bull's-eye and set the mean to By Michael Parker October 8, 1 When working with data sets in six sigma projects, often there will be a need to compare two groups to each other. Put the cursor in the Store sorted column s in box, highlight Array, and use Select to copy Array into said box. In the first data variable column entitled Delivery Days enter the data for Supplier A and then the data for Supplier B.
Double click on Median. A lower bound means that is the smallest the values can be, but it could be more.
In the first column entitled Defects, enter the data for the day shift and then the data for the night shift. Data entered should consist of a 1 for passed and a 0 for failed. The first variable entitled Younger contains 24 and There should always be as many critical values as tails and the signs should agree.
Insert 5 in the Number of trials box and.
The number of events is what we called the number of successes, but it is important to note that these are both whole numbers, not percents or proportions. Form conclusions. Name the first variable Question 1 Data and the other Answers 1. Copy Department into Factor with a double click. Those using Quick's worksheets should load Mini Chapter 15 on Hypothesis Testing of Population Proportions Problem I message: The population proportion is a type of mean so these problems use the one-sample mean test described by chapter 13 directions.