# Statistics

Suppose, in a study was conducted to see if receiving speeding violation and car phone use were independent. In this study, 755 drivers were surveyed. Out of 755, 70 had a speeding violation and 685 did not; 305 were car phone users and 450 were not.

Car phone user Not a car phone user Total:

Received speeding violation 38 32 70

Did not received speeding violation 267 418 685

Total: 305 450 755

Use a 5% level of significance, to see if receiving speeding violation is independent of car phone use?

**EXPECTATIONS**

- Draw graphs and charts when appropriate and necessary to demonstrate your reasoning! Label all graphs and charts!

- Display formulas. Write complete sentences to summarize your conclusions.

- If use any table values, clearly state which tables you used (e.g. Table A-2, etc.).

-Attach excel output when appropriate or necessary (e.g. a scatterplot, etc.)

**HYPOTHESIS TESTING QUESTIONS**

Your work for all statistical hypothesis testing questions should include the following:

1. Established Ho and Ha.

2. Summary statistics (either computed or given in the problem)

3. The name of the test (e.g. 2sampleTtest or T-test about correlation, etc.)

4. A formula to compute a test statistic (e.g. 1Prop-Z test statistic, etc.)

5. A p-value of the test and/or a critical value from a statistical table.

6. Clearly state the decision rule you use the reach a conclusion. (You may have to sketch a graph to show rejection regions.) Do you “Reject Ho” or do you “Fail to Reject Ho”?

7. State your conclusion in plain language. Use complete sentences.

Answer rating (rated one time)

## Please see the attachment for solution.

body preview (16 words)

Please xxx the attachment xxx solution. xx xxx need any xxxxxxx clarification please xxx xxx xxxxxxx

file1.doc preview (877 words)

xxxxxxxx xx x study was xxxxxxxxx xx xxx if xxxxxxxxx speeding violation xxx xxx xxxxx xxx xxxx independent. In this study, 755 xxxxxxx were surveyed. xxx xx 755, 70 xxx x xxxxxxxx violation and xxx did xxxx xxx were car phone users xxx xxx were xxxxxxx

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file2.pdf preview (394 words)

Suppose, xx x xxxxx was conducted to xxx if receiving speeding violation and car phone use xxxx independent. In xxxx study, 755 drivers xxxx xxxxxxxxx xxx xx 755, 70 had a speeding violation and 685 did not; 305 were xxx xxxxx users xxx 450 xxxx not. xxx xxxxx user xxx a car phone xxxx Total: xxxxxxxx xxxxxxxx xxxxxxxxx xx xx 70 xxx not received xxxxxxxx violation xxx 418 xxx xxxxxx 305 xxx xxx xxx x xx xxxxx of significance, to see xx xxxxxxxxx speeding xxxxxxxxx is xxxxxxxxxxx of car phone use?

Solution

The xxxx xxx alternative hypotheses are Ho: xxxxxxxxx xxxxxxxx violation is xxxxxxxxxxx of car xxxxx use. xxx xxxxxxxxx speeding xxxxxxxxx xx xxx independent of car xxxxx xxxx Here, we xxx the Chi-Square xxxx for independence. xxx test xxxxxxxxx

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file3.xls preview (89 words)

# xxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxChi-Square Test | |||||

Observed xxxxxxxxxxx | Calculations | ||||

xxx xxxxx user | xxx a xxx phone xxxx | xxxxx | O-E | ||

xxxxxxxx xxxxxxxx xxxxxxxxx | 38 | xx | xx | 9.7219 | xxxxxxx |

Did not xxxxxxxx speeding xxxxxxxxx | xxx | 418 | 685 | xxxxxxx | 9.7219 |

Total | 305 | xxx | 755 | ||

xxxxxxxx Frequencies | |||||

Car xxxxx user | xxx a xxx xxxxx user | xxxxx | (O-E)^2/E | ||

xxxxxxxx xxxxxxxx xxxxxxxxx | 28.28 | xxxxx | xx | xxxxxx | xxxxxx |

Did not received speeding xxxxxxxxx | xxxxxx | xxxxxx | xxx | xxxxxx | 0.2315 |

Total | xxx | xxx | 755 | ||

Data | |||||

xxxxx of Significance | 0.05 | ||||

xxxxxx of Rows | 2 | ||||

xxxxxx xx xxxxxxx | x | ||||

xxxxxxx xx Freedom | x | ||||

Results | |||||

xxxxxxxx xxxxx | xxxxx | ||||

Chi-Square Test xxxxxxxxx | xxxxxx | ||||

xxxxxxx | xxxxxx | ||||

xxxxxx the xxxx hypothesis | |||||

Expected xxxxxxxxx xxxxxxxxxx | |||||

xx xxxx |

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