QNT561 University of Phoenix Manufacturing Database Case Worksheet

QNT561

University of Phoenix

### Question Description

This signature assignment is designed to align with specific program student learning outcome(s) in your program. Program Student Learning Outcomes are broad statements that describe what students should know and be able to do upon completion of their degree. The signature assignments might be graded with an automated rubric that allows the University to collect data that can be aggregated across a location or college/school and used for program improvements.

Purpose of Assignment

The purpose of this assignment is for students to synthesize the concepts learned throughout the course. This assignment will provide students an opportunity to build critical thinking skills, develop businesses and organizations, and solve problems requiring data by compiling all pertinent information into one report.

Assignment Steps

Resources: Microsoft Excel®, Signature Assignment Databases, Signature Assignment Options, Part 3: Inferential Statistics

Scenario: Upon successful completion of the MBA program, say you work in the analytics department for a consulting company. Your assignment is to analyze one of the following databases:

• Manufacturing
• Hospital
• Consumer Food
• Financial

Select one of the databases based on the information in the Signature Assignment Options.

Provide a 1,600-word detailed, statistical report including the following:

• Explain the context of the case
• Provide a research foundation for the topic
• Present graphs
• Explain outliers
• Prepare calculations
• Conduct hypotheses tests
• Discuss inferences you have made from the results

This assignment is broken down into four parts:

• Part 1 - Preliminary Analysis
• Part 2 - Examination of Descriptive Statistics
• Part 3 - Examination of Inferential Statistics
• Part 4 - Conclusion/Recommendations

Part 1 - Preliminary Analysis (3-4 paragraphs)

Generally, as a statistics consultant, you will be given a problem and data. At times, you may have to gather additional data. For this assignment, assume all the data is already gathered for you.

State the objective:

• What are the questions you are trying to address?

Describe the population in the study clearly and in sufficient detail:

• What is the sample?

Discuss the types of data and variables:

• Are the data quantitative or qualitative?
• What are levels of measurement for the data?

Part 2 - Descriptive Statistics (3-4 paragraphs)

Examine the given data.

Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and five-number summary).

Identify any outliers in the data.

Present any graphs or charts you think are appropriate for the data.

Note: Ideally, we want to assess the conditions of normality too. However, for the purpose of this exercise, assume data is drawn from normal populations.

Part 3 - Inferential Statistics (2-3 paragraphs)

Use the Part 3: Inferential Statistics document.

• Create (formulate) hypotheses
• Run formal hypothesis tests
• Make decisions. Your decisions should be stated in non-technical terms.

Hint: A final conclusion saying "reject the null hypothesis" by itself without explanation is basically worthless to those who hired you. Similarly, stating the conclusion is false or rejected is not sufficient.

Part 4 - Conclusion and Recommendations (1-2 paragraphs)

Include the following:

• What do you infer from the statistical analysis?
• State the interpretations in non-technical terms. What information might lead to a different conclusion?
• Are there any variables missing?
• What additional information would be valuable to help draw a more certain conclusion?

Format your assignment consistent with APA format.

This database contains six variables taken from 20 industries and 140 subindustries in the United States. Some of the industries are food products, textile mill products, furniture, chemicals, rubber products, primary metals, industrial machinery, and transportation equipment. The six variables are Number of Employees, Number of Production Workers, Value Added by Manufacture, Cost of Materials, End-of-Year Inventories, and Industry Group. Two variables, Number of Employees and Number of Production Workers, are in units of 1000. Three variables, Value Added by Manufacture, Cost of Materials, and End-of-Year Inventories, are in million-dollar units. The Industry Group variable consists of numbers from 1 to 20 to denote the industry group to which the particular subindustry belongs.

Option 2: Hospital Database

This database contains observations for six variables on U.S. hospitals. These variables include Geographic Region, Control, Service, Census, Number of Births, and Personnel.

The region variable is coded from 1 to 7, and the numbers represent the following regions:

1 = South

2 = Northeast

3 = Midwest

4 = Southwest

5 = Rocky Mountain

6 = California

7 = Northwest

Control is a type of ownership. Four categories of control are included in the database:

1 = government, nonfederal

2 = nongovernment, not-for-profit

3 = for-profit

4 = federal government

Service is the type of hospital. The two types of hospitals used in this database are:

1 = general medical

2 = psychiatric

Option 3: Consumer Food

The consumer food database contains five variables: Annual Food Spending per Household, Annual Household Income, Non-Mortgage Household Debt, Geographic Region of the U.S. of the Household, and Household Location. There are 200 entries for each variable in this database representing 200 different households from various regions and locations in the United States. Annual Food Spending per Household, Annual Household Income, and Non-Mortgage Household Debt are all given in dollars. The variable Region tells in which one of four regions the household resides. In this variable, the Northeast is coded as 1, the Midwest is coded 2, the South is coded as 3, and the West is coded as 4. The variable Location is coded as 1 if the household is in a metropolitan area and 2 if the household is outside a metro area. The data in this database were randomly derived and developed based on actual national norms.

Option 4: Financial Database

The financial database contains observations on seven variables for 100 companies. The variables are Type of Industry, Total Revenues (\$ millions), Total Assets (\$ millions), Return on Equity (%), Earnings per Share (\$), Dividends per Share (\$), and Average Price per Earnings (P/E) ratio. The companies represent seven different types of industries. The variable Type displays a company's industry type as:

1 = apparel

2 = chemical

3 = electric power

4 = grocery

5 = healthcare products

6 = insurance

7 = petroleum

 SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials End Yr. Inven. Indus. Grp. 201 433 370 23518 78713 3630 1 202 131 83 15724 42774 3157 1 203 204 169 24506 27222 8732 1 204 100 70 21667 37040 3407 1 205 220 137 20712 12030 1155 1 206 89 69 12640 13674 3613 1 207 26 18 4258 19130 1946 1 208 143 72 35210 33521 7199 1 209 171 126 20548 19612 3135 1 211 21 15 23442 5557 5506 2 212 3 2 287 163 42 2 213 2 2 1508 314 155 2 214 6 4 624 2622 554 2 221 52 47 2471 4219 929 3 222 74 63 4307 5357 1427 3 223 13 12 673 1061 325 3 224 17 13 817 707 267 3 225 169 147 8986 10421 2083 3 226 51 41 3145 4140 697 3 227 55 44 4076 7125 1446 3 228 84 76 3806 8994 1014 3 229 61 47 4276 5504 1291 3 231 27 22 1239 716 356 4 232 200 178 9423 8926 2314 4 233 294 250 11045 11121 2727 4 234 38 32 1916 2283 682 4 235 17 14 599 364 197 4 236 34 28 2063 1813 450 4 237 1 1 34 71 17 4 238 31 25 1445 1321 526 4 239 224 179 10603 12376 2747 4 241 83 68 5775 9661 578 5 242 172 147 10404 19285 3979 5 243 257 209 13274 18632 3329 5 244 51 43 1909 2170 355 5 245 82 68 4606 7290 580 5 249 94 78 5518 8135 1604 5 251 273 233 12464 12980 3535 6 252 70 53 5447 4011 829 6 253 37 29 2290 5101 447 6 254 81 61 4182 3755 956 6 259 54 39 2818 2694 718 6 261 15 11 2201 3279 725 7 262 116 90 18848 20596 4257 7 263 55 42 9655 10604 1502 7 265 212 163 15668 24634 3976 7 267 232 182 25918 28963 5427 7 271 403 136 30692 8483 894 8 272 121 16 17982 6940 1216 8 273 136 57 17857 8863 3736 8 274 69 25 9699 2823 874 8 275 604 437 38407 29572 4300 8 276 41 28 3878 3811 688 8 277 21 12 3989 1047 577 8 278 65 50 4388 2055 504 8 279 55 39 4055 1098 236 8 281 80 45 16567 11298 2644 9 282 115 79 25025 34596 6192 9 283 213 106 59813 27187 11533 9 284 126 75 31801 19932 4535 9 285 51 28 8497 9849 2178 9 286 126 75 28886 46935 8577 9 287 37 24 12277 11130 2354 9 289 76 45 11547 13085 2749 9 291 67 43 26006 132880 10718 10 295 25 18 3464 6182 658 10 299 14 8 2187 4446 670 10 301 65 54 7079 7091 1067 11 302 8 7 442 496 175 11 305 61 46 4528 3805 1057 11 306 122 95 7275 7195 1411 11 308 763 598 55621 57264 11874 11 311 15 12 1313 1865 404 12 313 3 2 162 163 35 12 314 37 31 1907 1682 716 12 315 2 2 53 85 62 12 316 6 4 747 395 199 12 317 8 7 328 255 75 12 319 7 6 233 177 40 12 321 12 9 1717 943 282 13 322 60 51 6532 3527 1505 13 323 64 50 4850 4254 883 13 324 17 13 3509 2282 828 13 325 31 25 2176 1387 700 13 326 45 36 2696 1183 600 13 327 205 152 15739 17010 1966 13 328 17 13 999 565 263 13 329 72 53 7838 5432 1652 13 331 221 174 29180 45696 12198 14 332 128 106 9061 6913 1543 14 333 35 26 4200 11184 1834 14 334 15 11 1410 5735 694 14 335 162 123 16670 31892 6377 14 336 94 79 5856 4696 938 14 339 32 23 3164 2790 800 14 341 33 27 3999 9364 1453 15 342 140 107 11750 8720 3124 15 343 45 32 4412 3527 1121 15 344 432 315 27974 31527 7204 15 345 104 81 6936 4909 1768 15 346 259 211 19880 21531 3997 15 347 129 99 7793 6232 1181 15 348 40 24 3528 1689 1077 15 349 300 219 21718 19273 6460 15 351 79 55 10513 12954 3679 16 352 94 70 9545 11858 3339 16 353 205 133 18178 23474 7344 16 354 295 211 22673 14343 6730 16 355 192 110 19221 16515 6823 16 356 265 172 23110 18543 7898 16 357 259 96 41135 60857 10277 16 358 201 147 17521 21819 4857 16 359 392 293 25322 13897 4964 16 361 74 51 6700 5523 1495 17 362 171 120 14278 12657 3887 17 363 108 87 9466 12578 2299 17 364 157 117 13428 11065 3076 17 365 49 37 3459 7621 1070 17 366 258 120 38705 29591 9467 17 367 588 368 84059 44486 13145 17 369 151 106 13920 13398 3514 17 371 772 634 105899 223639 15852 18 372 377 190 45220 42367 36814 18 373 141 108 7903 7760 2165 18 374 31 23 2590 4363 1233 18 375 18 14 1435 1674 412 18 376 81 29 9986 8120 4770 18 379 47 35 3564 5476 1102 18 381 186 68 21071 8760 6183 19 382 272 141 29028 18028 7681 19 384 268 157 31051 16787 7761 19 385 27 17 2390 1020 426 19 386 61 36 14032 8114 2290 19 387 6 4 415 382 177 19 391 43 30 2761 3646 1451 20 393 13 10 685 506 328 20 394 103 76 8327 6604 2608 20 395 35 26 2643 1789 799 20 396 24 19 1406 997 415 20 399 179 123 11199 8530 2861 20

Part 3: Inferential Statistics

Option 1: Manufacturing Database

• The National Association of Manufacturers (NAM) contracts with your consulting company to determine the estimate of mean number of production workers. Construct a 95% confidence interval for the population mean number of production workers. What is the point estimate? How much is the margin of error in the estimate?
• Suppose the average number of employees per industry group in the manufacturing database is believed to be less than 150 (1000s). Test this belief as the alternative hypothesis by using the 140 SIC Code industries given in the database as the sample. Let α = .10. Assume that the number of employees per industry group are normally distributed in the population.
• You are also required to determine whether there is a significant difference between mean Value Added by the Manufacturer and the mean Cost of Materials in manufacturing using alpha of 0.01.
• You are requested to determine whether there is a significantly greater variance among values of Cost of Materials than of End-of-Year Inventories.

Option 2: Hospital Database

• As a consultant, you need to use the Hospital database and construct a 90% confidence interval to estimate the average census for hospitals. Change the level of confidence to 99%. What happened to the interval? Did the point estimate change?
• Determine the sample proportion of the Hospital database under the variable “service” that are “general medical” (category 1). From this statistic, construct a 95% confidence interval to estimate the population proportion of hospitals that are “general medical.” What is the point estimate? How much error is there in the interval?
• Suppose you want to “prove” that the average hospital in the United States averages more than 700 births per year. Use the hospital database as your sample and test this hypothesis. Let alpha be 0.01.
• On average, do hospitals in the United States employ fewer than 900 personnel? Use the hospital database as your sample and an alpha of 0.10 to test this figure as the alternative hypothesis. Assume that the number of births and number of employees in the hospitals are normally distributed in the population.

Option 3: Consumer Food

• Suppose you want to test to determine if the average annual food spending for a household in the Midwest region of the U.S. is more than \$8,000. Use the Midwest region data and a 1% level of significance to test this hypothesis. Assume that annual food spending is normally distributed in the population.
• Test to determine if there is a significant difference between households in a metro area and households outside metro areas in annual food spending. Let α = 0.01.
• The Consumer Food database contains data on Annual Food Spending, Annual Household Income, and Non-Mortgage Household Debt broken down by Region and Location. Using Region as an independent variable with four classification levels (four regions of the U.S.), perform three different one-way ANOVA's—one for each of the three dependent variables (Annual Food Spending, Annual Household Income, Non-Mortgage Household Debt). Did you find any significant differences by region?

Option 4: Financial Database

• Use this database as a sample and estimate the earnings per share for all corporations from these data. Select several levels of confidence and compare the results.
• Are the average earnings per share for companies in the stock market less than \$2.50? Use the sample of companies represented by this database to test that hypothesis. Let α = .05.
• Test to determine whether the average return on equity for all companies is equal to 21. Use this database as the sample and α = .10. Assume that the earnings per share and return on equity are normally distributed in the population.
• Do various financial indicators differ significantly according to type of company? Use a one-way ANOVA and the financial database to answer this question. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum). Compute three one-way ANOVAs, one for each of the following dependent variables: Earnings Per Share, Dividends Per Share, and Average P/E Ratio.

Part 3: Inferential Statistics

Option 1: Manufacturing Database

• The National Association of Manufacturers (NAM) contracts with your consulting company to determine the estimate of mean number of production workers. Construct a 95% confidence interval for the population mean number of production workers. What is the point estimate? How much is the margin of error in the estimate?
• Suppose the average number of employees per industry group in the manufacturing database is believed to be less than 150 (1000s). Test this belief as the alternative hypothesis by using the 140 SIC Code industries given in the database as the sample. Let α = .10. Assume that the number of employees per industry group are normally distributed in the population.
• You are also required to determine whether there is a significant difference between mean Value Added by the Manufacturer and the mean Cost of Materials in manufacturing using alpha of 0.01.
• You are requested to determine whether there is a significantly greater variance among values of Cost of Materials than of End-of-Year Inventories.

Option 2: Hospital Database

• As a consultant, you need to use the Hospital database and construct a 90% confidence interval to estimate the average census for hospitals. Change the level of confidence to 99%. What happened to the interval? Did the point estimate change?
• Determine the sample proportion of the Hospital database under the variable “service” that are “general medical” (category 1). From this statistic, construct a 95% confidence interval to estimate the population proportion of hospitals that are “general medical.” What is the point estimate? How much error is there in the interval?
• Suppose you want to “prove” that the average hospital in the United States averages more than 700 births per year. Use the hospital database as your sample and test this hypothesis. Let alpha be 0.01.
• On average, do hospitals in the United States employ fewer than 900 personnel? Use the hospital database as your sample and an alpha of 0.10 to test this figure as the alternative hypothesis. Assume that the number of births and number of employees in the hospitals are normally distributed in the population.

Option 3: Consumer Food

• Suppose you want to test to determine if the average annual food spending for a household in the Midwest region of the U.S. is more than \$8,000. Use the Midwest region data and a 1% level of significance to test this hypothesis. Assume that annual food spending is normally distributed in the population.
• Test to determine if there is a significant difference between households in a metro area and households outside metro areas in annual food spending. Let α = 0.01.
• The Consumer Food database contains data on Annual Food Spending, Annual Household Income, and Non-Mortgage Household Debt broken down by Region and Location. Using Region as an independent variable with four classification levels (four regions of the U.S.), perform three different one-way ANOVA's—one for each of the three dependent variables (Annual Food Spending, Annual Household Income, Non-Mortgage Household Debt). Did you find any significant differences by region?

Option 4: Financial Database

• Use this database as a sample and estimate the earnings per share for all corporations from these data. Select several levels of confidence and compare the results.
• Are the average earnings per share for companies in the stock market less than \$2.50? Use the sample of companies represented by this database to test that hypothesis. Let α = .05.
• Test to determine whether the average return on equity for all companies is equal to 21. Use this database as the sample and α = .10. Assume that the earnings per share and return on equity are normally distributed in the population.
• Do various financial indicators differ significantly according to type of company? Use a one-way ANOVA and the financial database to answer this question. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum). Compute three one-way ANOVAs, one for each of the following dependent variables: Earnings Per Share, Dividends Per Share, and Average P/E Ratio.

Attached.

MANUFACTURING DATABASE
Name:
Institution affiliation:
Date:

1

MANUFACTURING DATABASE

2

Part I: Preliminary Analysis
Objective
The key goals of this research are:

To determine the average number of production workers.

To verify if the mean number of workers per industry group is less than 150 (1000s).

To construct a 95% confidence interval for the population mean number of production
workers.

To evaluate if a significant difference exists between the mean Cost of Materials in
manufacturing and mean Value Added by the Manufacturer.

To evaluate if there is a significant difference in variance between Cost of Materials as
compared to the End-of-Year Inventories.

Population
The dataset consists of 6 variables obtained from 20 industries and 140 sub-industries in
the U.S. The variables include; the Number of Employees, Number of Production Workers,
Value Added by Manufacture, Cost of Materials. End-of-Year Inventories, and Industry Groups.
The two variables, i.e., the Number of Production Workers and Number of Employees are in
units of 1000. Three variables, i.e., Cost of Materials, Value Added by Manufacture, and End-ofYear Inventories are in million-dollar units. The Industry Group variable consists of numbers
from 1-20 to denote the industry group to which the specific sub-industry belongs.
Data & variables
The provided data is qualitative in the sense that it consists of measurable numbers. The
five qualitative variables in the data set are No. Emp., No. Prod. Wkrs., Value Added by Mfg.,
Cost of Materials, and End Yr. Inven. These variables were measured on a ratio scale of

MANUFACTURING DATABASE

3

measurement. Indus. On the other hand, the Indus. Grp. is a qualitative variable that is measured
on a nominal scale of measurement.

Part II: Descriptive Statistics
The following table provides a summary of the mean, mode, median, standard deviation, range,
CV, variance, and five-number summary.
Value
No.

No. Prod.

Cost of

End Yr.

Emp.

Wkrs.

Mfg.

Materials

Inven.

Indus. Grp.

mean

123.7929 86.95714286

12497.67857 14109.77143 3050.792857 10.557143

median

75

52

7534

7455.5

1498.5

11

mode

17

2

#N/A

163

#N/A

1

minimum

1

1

34

71

17

1

maximum

772

634

105899

223639

36814

20

range

771

633

105865

223568

36797

19

standard

138.0624 102.1639162

15340.69054 24569.91329 4242.622069 5.8312868

variance

19061.22 10437.46578

235336786.3 603680639.1 17999842.02 34.003905

CV

112%

117%

123%

174%

139%

55%

1st quartile

33.75

24.75

2682.75

2676

686.5

5

3rd quartile

171.25

117.75

17888.25

16583

3773.75

16

93

15205.5

13907

3087.25

11

257.25

40696.5

37443.5

8404.625

32.5

-114.75

-20125.5

-18184.5

-3944.375

-11.5

deviation

interquartile 137.5
range
UPPER

377.5

bound
Lower bond -172.5

MANUFACTURING DATABASE

4

From the above table, the mean of the number of Employees, number of Production
Workers, value Added by Manufacturer, Cost of Materials, and End-of-Year Inventories is
123.79, 86.5, 12497.68, 14109.77, and 3050.79 respectively. On the other hand, the median for
the Number of Employees, Number of Production Workers, value Added by Manufacture, Cost
of Materials and End-of-Year Inventories is 75, 52, 7534, 7455.5 and 1498.5 respectively. The
value of standard deviation is high, implying the unreliability of mean and probable existence of
outliers in the data set. Almost all variables have a high value of standard deviation except Indus.
Grp.
Outliers
Outliers are data points that vary significantly from the rest of the data points. The
presence of outliers indicates an uneven distribution of data or the presence of errors. The data
set comprises of several outliers. Both the Number of Employees and Number of Production
Workers have 8 outliers. The Value Added by Manufacturer has 6 outliers, Cost of Material
has10 outliers, and End of Year Inventories consists of 11 outliers.
Charts
Histogram

MANUFACTURING DATABASE

5

From the above histograms, it is evident that the data for Number of Production Workers,
Number of Employees, Cost of Materials, value Added by Manufacture, and End-of-Year
Inventories is skewed to the right. In this case, only a few observations have high values.

The boxplot
The figure below presents the box plot for Number of Employees, Number of Production
Workers, value Added by Manufacture, Cost of Materials, and End-of-Year Invento...

JesseCraig (16616)
Purdue University
Review

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Anonymous
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