# Project #9074 - Statistics

Problem C – Analysis of Variance, Chapter 11, Section 11.1
Compute using: Data Analysis Tookpak, Anova single factor

You have worked with numerous hospitals on performance improvements in order to enhance organizational efficiency and effectiveness. You have a current hospital client who has contacted you to assist them with emergency room efficiency. The hospital conducted a study of the waiting time in its emergency room. The hospital has a main campus and three satellite locations. The hospital executive managers have established a business objective of reducing waiting time for emergency room cases that did not require immediate attention. To study this, a random sample of 15 emergency room cases that did not require immediate attention at each location were selected on a particular day, and the waiting time (measured from check-in to when the patient was called into the clinic area) was measured.

 Main Satellite 1 Satellite 2 Satellite 3 120.08 30.75 75.86 54.05 81.90 61.83 37.88 38.82 78.79 26.40 68.73 36.85 63.83 53.84 51.08 32.83 79.77 72.30 50.21 52.94 47.94 53.09 58.47 34.13 79.88 27.67 86.29 69.37 48.63 52.46 62.90 78.52 55.43 10.64 44.84 55.95 64.06 53.50 64.17 49.61 64.99 37.28 50.68 66.40 53.82 34.31 47.97 76.06 62.43 66.00 60.57 11.37 65.07 8.99 58.37 83.51 81.02 29.75 30.40 39.17

1. At the 0.05 level of significance, is there evidence of a difference in the mean waiting times in the four locations?

1. State the null hypothesis and alternative hypothesis

2. State the decision rule

3. Report the results/finding of your data analysis

2. Provide your client with your interpretation of the organizational problem based on the initial organizational diagnostic and assessment data. What additional information do you need in order to complete the organizational diagnosis and make a recommendation for an organizational improvement project? Why is this important to the success of the improvement initiative?

Problem E – Analysis of Variance, Chapter 11, Section 11.2
Compute using: Data Analysis Tookpak, Anova Two factor with replication

 Type Four Eight A 265 310 A 270 320 I 250 300 I 245 305

A chef in a restaurant that specializes in pasta dishes was experiencing difficulty in getting brands of pasta to be al dente – that is, cooked enough so as not to feel starchy or hard but still feel firm when bitten into. She decided to conduct an experiment in which two brands of pasta, one American and one Italian, were cooked for either 4 or 8 minutes. The variable of interest was weight of the pasta because cooking the pasta enables it to absorb water. A pasta with a faster rate of water absorption may provide a shorter interval in which the pasta is al dente, thereby increasing the chance that it might be overcooked. The experiment was conducted by using 150 grams of uncooked pasta. Each trial began by bringing a pot containing 6 quarts of cold, unsalted water to a moderate boil. The 150 grams of uncooked pasta was added and then weighed after a given period of time by lifting the pasta from the pot via a built-in strainer. The results (in terms of weight in grams) for two replicates of each type of pasta and cooking time are provided to you.

Cooking Time (in minutes) Type 4 8

American 265 310 American 270 320 Italian 250 300 Italian 245 305

At the 0.05 level of significance,

1. Is a.b. c. d.

2. Is a. b. c.

3. Is a. b. c.

there an interaction between type of pasta and cooking time? State the null hypothesis and alternative hypothesis.

State the decision rule
Report the test statistic
Report the results/findings of your statistical analysis

there an effect due to type of pasta?
State the decision rule
Report the test statistic
Report the results/findings of your statistical analysis

there an effect due to cooking time?
State the decision rule
Report the test statistic
Report the results/findings of your statistical analysis

4. What conclusions can you reach concerning the importance of these two factors on the weight of the pasta?

Problem G – Chi-square, Chapter 12, Section 12.1 Data: Use the data in the problem
Compute using: Chi-square.xls

A sample of 500 shoppers was selected in a large metropolitan area to collect information concerning consumer behavior. Among the questions asked was, “Do you enjoy shopping for clothing?” The results are summarized in the following contingency table:

 Enjoy Shopping for Clothing Male Female Total Yes 136 224 360 No 104 36 140 Total 240 260 500

1. Is there evidence of a significant difference between the proportion of males and females who enjoy shopping for clothing at the 0.01 level of significance?

State the decision rule.

Report the test statistic

Report your findings/results of your data analysis.

1. Determine the p-value and interpret its meaning.

2. If 206 males enjoyed shopping for clothing and 34 did not, is there evidence of a significant difference between the proportion of males and females who enjoy shopping for clothing at the 0.01 level of significance?

3. If 206 males enjoyed shopping for clothing and 34 did not, determine the p-value and interpret its meaning.

4. If you were an organizational consultant for the business who conducted this survey, how would you use these data in an organizational diagnosis? What additional information would you want to conduct a complete organizational diagnosis in order to make a project improvement recommendation? Why is this important?

 Subject Mathematics Due By (Pacific Time) 07/15/2013 12:00 am
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