BUSN 5760 Mid Term

Game Attendance Promotion Z - Scores No Promotion Stats2 10856 N -0.693952 Statistics4 15178 N 0.279928 Sample Size 37

10 11125 N -0.633338 Mean 13935.711 11825 N -0.475606 Median 1295215 12555 N -0.311115 Std. Deviation 4437.9218 12389 N -0.34852 Minimum 955519 12334 N -0.360913 Maximum 2883420 12620 N -0.29646825 11773 N -0.48732426 13662 N -0.061674 A. see no promotion labels30 13493 N -0.099755 B. Mean: 13935.7 Median: 12952 1st Q: 11779 31 12963 N -0.21918 3rd Q: 14367 Range: 2588 SD: 4437.9232 14057 N 0.027332 C. See Z Scores to left and game 59 and 60 are potential outliers33 12952 N -0.221659 D. With promotions there was a lot more attendance but with the higher SD I would say there was more unpredictability to the attendance then when there34 12828 N -0.2496 is no promotion.35 16373 N 0.549198 Boxplot NO PROMOTION39 13031 N -0.20385745 14677 N 0.167037 Five-Number Summary46 13823 N -0.025395 Minimum 955547 15522 N 0.357442 First Quartile 1177952 14759 N 0.185514 Median 1295253 13066 N -0.195971 Third Quartile 1436754 13461 N -0.106965 Maximum 2883455 12669 N -0.28542759 28834 N 3.35704560 26383 N 2.80475961 27565 N 3.071162 11785 N -0.4846266 11096 N -0.63987267 13077 N -0.19349268 15952 N 0.45433472 9555 N -0.98710773 10106 N -0.8629574 12104 N -0.41273978 9878 N -0.91432579 10203 N -0.84109380 11092 N -0.640774

1 40605 Y 2.4484963 15975 Y -0.5886845 10788 Y -1.2283046 24456 Y 0.4571277 22264 Y 0.1868278 17289 Y -0.4266529 10470 Y -1.267518

12 12372 Y -1.03297813 16850 Y -0.48078614 15643 Y -0.62962416 24279 Y 0.435301

17 10820 Y -1.22435821 24055 Y 0.40767922 20062 Y -0.08470723 21740 Y 0.12221124 21740 Y 0.12221127 34194 Y 1.65794128 40016 Y 2.37586529 26905 Y 0.75911936 29935 Y 1.13275537 27441 Y 0.82521438 22073 Y 0.16327440 24824 Y 0.50250641 19504 Y -0.15351542 12457 Y -1.02249643 14905 Y -0.72062844 14905 Y -0.72062848 20922 Y 0.02134249 36277 Y 1.91480150 36277 Y 1.91480151 15637 Y -0.63036356 23003 Y 0.27795457 18213 Y -0.31271158 15527 Y -0.64392863 29685 Y 1.10192764 22180 Y 0.17646865 13440 Y -0.9012869 13363 Y -0.91077570 19775 Y -0.12009771 11442 Y -1.14765875 13271 Y -0.9221276 15448 Y -0.65366977 11177 Y -1.180336

Promotion StatsStatistics

Sample Size 43Mean 20748.93Median 19775Std. Deviation 8109.497Minimum 10470Maximum 40605

see promotion labelsMean: 13935.7 Median: 12952 1st Q: 11779 Mean: 20748.93 Median: 19775 1st Q: 149053rd Q: 14367 Range: 2588 SD: 4437.92 3rd Q: 24279 Range: 9374 SD: 8109.497See Z Scores to left and game 59 and 60 are potential outliers See Z Scores to left games 1 and 29 could be potential outliersWith promotions there was a lot more attendance but with the higher SD I would say there was more unpredictability to the attendance then when there

Promotion

Five-Number SummaryMinimum 10470First Quartile 14905Median 19639.5Third Quartile 24279Maximum 40016

With promotions there was a lot more attendance but with the higher SD I would say there was more unpredictability to the attendance then when there

Boxplot NO PROMOTION

Five-Number SummaryMinimum 9555First Quartile 11779Median 12952Third Quartile 14367Maximum 28834

9550 14550 19550 24550 29550

1

2

3

Boxplot

No Promotion

Stem unit: 1000

Statistics 9 6 9Sample Size 37 10 1 2 9Mean 13935.7 11 1 1 1 8 8 8Median 12952 12 1 3 4 6 6 7 8Std. Deviation 4437.92 13 0 0 0 1 1 5 5 7 8Minimum 9555 14 1 7 8Maximum 28834 15 2 5

16 0 417181920212223242526 427 628 8

Promotion

Five-Number SummaryMinimum 10470First Quartile 14905Median 19639.5Third Quartile 24279Maximum 40016

10460 15460 20460 25460 30460 35460 40460

1

2

3

Promotion

Promotion

Stem unit: 1000

Statistics 10 5 8 8Sample Size 43 11 2 4Mean 20748.93 12 4 5Median 19775 13 3 4 4Std. Deviation 8109.497 14 9 9Minimum 10470 15 4 5 6 6Maximum 40605 16 0 9

17 318 219 5 820 1 921 7 722 1 2 323 024 1 3 5 82526 927 42829 7 93031323334 23536 3 337383940 0 6

Defective Refrigerator Compressor

DataSample size 8No. of events of interest in population 9Population size 15

Hypergeometric Probabilities Table a. 0.000155X P(X) b. 0.2140 0 c. 0.11 0 d. 02 0.005594 e. See H Column3 0.0783224 0.2937065 0.3916086 0.1958047 0.0335668 0.001399

e.0

0.6220.0060.001

Problem 7.51

a. How was this survey conducted and how what are the age ranges of the respondentsb. Coverage Error happens when some groups are excluded from the survey and have no chance of being selected

Non response Error occurs when people do not respond and their reponse may differ from those who did respondSampling Error is the chance variation from sample to sampleMeasurement Error happens when the questions asked are weak and can be interpreted differently from repsondent torespondent or when the interviewer has influence over the respondant's answer

c. The Hawthorne effect is a type of measurement error that occurs when the respondent feels the need to give the interviewer the answer that the respondent feels the interviewer is looking for.

Coverage Error happens when some groups are excluded from the survey and have no chance of being selectedNon response Error occurs when people do not respond and their reponse may differ from those who did respond

Measurement Error happens when the questions asked are weak and can be interpreted differently from repsondent to

The Hawthorne effect is a type of measurement error that occurs when the respondent feels the need to give the interviewer the answer

Binomial Probabilities

DataSample size 15 a. 0.005Probability of an event of interest 0.15 b. 0.05

c. 0.515Statistics d. 0.653

Mean 2.25 e. Mean: 4.5 SD: 1.775Variance 1.9125 f. See Column IStandard deviation 1.382932 85% Pass or 15% Fail

Binomial Probabilities TableX P(X)

0 0.0873541 0.2312322 0.2856393 0.218434 0.1156395 0.0448956 0.0132057 0.0029968 0.0005299 7.257E-05

10 7.684E-0611 6.163E-0712 3.625E-0813 1.476E-0914 3.722E-1115 4.379E-13

15% Fail0.087

0.00060.9380.177

Mean: 2.25 SD: 1.383

5.

ACT Exam

Common Data a.Mean 21.4 b.Standard Deviation 5.3 c.

Probability for a Range d.Probability for X <= From X Value 19 e.

X Value 12 To X Value 24 f.Z Value -1.7735849 Z Value for 19 -0.45283P(X<=12) 0.0380659 Z Value for 24 0.490566

P(X<=19) 0.3253Probability for X > P(X<=24) 0.6881

X Value 34 P(19<=X<=24) 0.3628Z Value 2.3773585P(X>34) 0.0087 Find X and Z Given Cum. Pctage.

Cumulative Percentage 90.00%Probability for X<12 or X >34 Z Value 1.2815516

P(X<12 or X >34) 0.0468 X Value 28.192223

5.

0.2030.2490.3630.047

26.25128.192

What if example, section 5.5

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1.5 2 2.5 3 3.5 4 4.5 5 5.50

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1006. German

X

Y

6 Years StudTest Grade3 574 78 a. See 6. German Tab4 72 b. Correl: 0.911113 With a Correlation of .911 there appears to be a definate positive relationship between years2 58 studied and test scores5 89 c. Home work scores could also affect these scores or even attendance 3 634 735 843 752 48

With a Correlation of .911 there appears to be a definate positive relationship between yearsstudied and test scores

Home work scores could also affect these scores or even attendance

7. Poisson

Tornadoes in May

DataMean/Expected number of events of interest: 6

Poisson Probabilities Table a. 0.134X P(X) b. 0.9980 0.002479 c. 0.6721 0.014873 d. 0.982 0.0446183 0.0892354 0.1338535 0.1606236 0.1606237 0.1376778 0.1032589 0.068838

10 0.04130311 0.02252912 0.01126413 0.00519914 0.00222815 0.00089116 0.00033417 0.00011818 0.00003919 0.00001220 0.000004

Original Data

3

What if example, section 4.14.4

5

Probabilities Calculations

Sample Space Satisfied?yes satisfied not satisfied Totals

Got packages before X-Mas? yes by xmas 1012 98 1110no by xmas 218 172 390Totals 1230 270 1500

Simple ProbabilitiesP(yes by xmas) 0.74 a. see table aboveP(no by xmas) 0.26 b. Were the online customers satisified?P(yes satisfied) 0.82 c. were the online customers satisfied and did they receive packages by christmas?P(not satisfied) 0.18 d. Not satisfied with expierence

Joint Probabilities e. 82% 0.82P(yes by xmas and yes satisfie 0.67 f. 74% 0.74P(yes by xmas and not satisfie 0.07 g. 67.00% 0.67P(no by xmas and yes satisfied 0.15 h. 89% 0.89P(no by xmas and not satisfied 0.11 i. 33% 0.33

j. question g is where both events occur together and h is where the events do not overlap or not thogetherAddition Rule

P(yes by xmas or yes satisfied) 0.89P(yes by xmas or not satisfied) 0.85P(no by xmas or yes satisfied) 0.93P(no by xmas or not satisfied) 0.33

were the online customers satisfied and did they receive packages by christmas?

question g is where both events occur together and h is where the events do not overlap or not thogether

9a. The population is sampled for this survey by actual interviewers that return to the same residence every 2 years to record the information.

It does not matter if the tenants have moved. The interviewer will take the information from current tenants or from landlords regarding the needed informationb. Garage or Carport included with home and it is nominalc. Monthly Housing costs and it is a ratiod. Architects/investors or school districts/admissionse. taken directly from the website: The data in this report are subject to error from sampling and other causes, such as incomplete data and wrong answers.

Appendix D contains a complete description of the types of errors and provides formulas for constructing confidence intervals. With incomplete data there is coverage errors where the units surveyed do not adaquetly represent the average units of the area or country. There is also incomplete data where some repondents refuse to answer some or all the questions.

To help minimize the incomplete errors the interviewer can only interview respondents that agree to answer all the questions. As far as covereage error the interviewers could adjust the locations that are surveyed to units that represent the majority of the population.

The population is sampled for this survey by actual interviewers that return to the same residence every 2 years to record the information. It does not matter if the tenants have moved. The interviewer will take the information from current tenants or from landlords regarding the needed information

taken directly from the website: The data in this report are subject to error from sampling and other causes, such as incomplete data and wrong answers. Appendix D contains a complete description of the types of errors and provides formulas for constructing confidence intervals. With incomplete data there is coverage errors where the units surveyed do not adaquetly represent the average units of the area or country. There is also incomplete

To help minimize the incomplete errors the interviewer can only interview respondents that agree to answer all the questions. As far as covereage error the interviewers could adjust the

BUSN 5760 Mid Term

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