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?
- 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)
xxxxxx xxx the xxxxxxxxxx for xxxxxxxxx xx xxx xxxx xxx further clarification please xxx me. xxxxxxx
file1.doc preview (838 words)
xxxxxxxx in a xxxxx was xxxxxxxxx xx see if receiving speeding violation and car phone xxx xxxx independent. xx this study, 755 xxxxxxx were surveyed. Out of xxxx xx had a speeding xxxxxxxxx xxx 685 xxx not; xxx were xxx xxxxx xxxxx xxx xxx xxxx xxxxxxx xxx xxxxx user Not x xxx xxxxx user xxxxxxxxxxxxxxxxx xxxxxxxx violation
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file2.pdf preview (354 words)
xxxxxxxx xx a study xxx conducted xx xxx xx xxxxxxxxx xxxxxxxx violation and xxx xxxxx xxx xxxx xxxxxxxxxxxx xx this xxxxxx 755 xxxxxxx xxxx xxxxxxxxx xxx xx 755, 70 xxx x speeding violation xxx 685 did not; 305 xxxx xxx xxxxx xxxxx and 450 were xxxx xxx xxxxx xxxx Not a car xxxxx user Total: Received xxxxxxxx violation xx xx xx Did xxx xxxxxxxx speeding violation xxx 418 685 xxxxxx 305 450 755 Use a 5% level of significance, to xxx if xxxxxxxxx speeding violation xx xxxxxxxxxxx of xxx phone xxxx
The xxxx and xxxxxxxxxxx hypotheses xxx xxx xxxxxxxxx speeding violation xx xxxxxxxxxxx of car phone xxxx xxx Receiving xxxxxxxx xxxxxxxxx xx not xxxxxxxxxxx xx car xxxxx use. Here, xx xxx xxx Chi-Square xxxx xxx xxxxxxxxxxxxx xxx xxxx xxxxxxxxx is given xxx
2 2 x )O xx
xxxx −=∑ ,
where x is xxx observed xxxxxxxxx and E xx xxx xxxxxxxx xxxxxxxxx xx the xxxxxxx cell. xxxx xxx statistic xxx xxxxxxxxxx xxxxxxxxxxxx xxxx xxxxxxxxxx xxxxxxx xx
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file3.xls preview (78 words)
|Car xxxxx xxxxx||Not a Car phone userx||Total||O-E|
|xxxxxxxx xxxxxxxx xxxxxxxxx||xx||32||xxxx||9.7219||xxxxxxx|
|Did xxx received speeding violation||267x||418x||685xx||xxxxxxxx||xxxxxx|
|Car xxxxx user||Not x xxx xxxxx xxxx||xxxxx||(O-E)^2/E|
|xxxxxxxx xxxxxxxx violationx||xxxxxx||41.72||70xx||3.3423x||2.2653|
|xxx not received speeding xxxxxxxxx||xxxxxx||408.28x||685xx||0.3416x||0.2315|
|Level of xxxxxxxxxxxxx||0.05|
|Number xx Rowsx||2|
|xxxxxx of xxxxxxx||2|
|Degrees xx xxxxxxx||x|
|Chi-Square Test Statistic||xxxxxx|
|Reject the null xxxxxxxxxx|
|xxxxxxxx xxxxxxxxx assumption|
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