Evaluate the confidence interval for the slope

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Reference no: EM138122

1. A researcher was interested in determining whether incentives, and how they were offered, affected the response rate in surveys. A simple random sample of 50 adult residents of a large city was selected. All were mailed a survey. In half of the mailings a check was included as a token of appreciation (in advance) for completing the survey. Five of these checks were for $1.00, five were for $5.00, five were for $10.00, five were for $25.00, and five were for $50.00. In the other half, people were promised a check upon returning a completed survey. Five were promised a check for $1.00, five were promised a check for $5.00, five were promised a check for $10.00, five were promised a check for $25.00, and five were promised a check for $50.00. Which method of payment (check enclosed or check to be sent upon return of a completed survey) and the amount ($1.00, $5.00, $10.00, $25.00, or $50.00) each person received was determined by randomization. For each person who was sent one of the surveys, the researcher recorded whether or not a completed survey was returned.

Let x be the amount of the check (either enclosed or promised) and z be the indicator variable

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We wish to fit a logistic regression model

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where p is the binomial probability of returning a completed survey, and log is the natural logarithm. The multiple logistic regression output from fitting this model is given below.

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A 95% confidence interval for the slope β1 is

A. 0.05903 ± 0.042156.
B. 0.05903 ± 0.02151.
C. -1.01641 ± 0.90260.

2. An SRS of 400 adults was taken. Each person was asked whether they had ever purchased an item over the internet. The gender of each person was also recorded. The results were

1515_Evaluate the confidence interval for the slope.png

The odds that someone who has purchased an item over the internet is a male is

A. 0.63.
B. 1.7.
C. 1.22.

Reference no: EM138122

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Example on natural logarithm : where p is the binomial probability of returning a completed survey, and log is the natural logarithm. The multiple logistic regression output from fitting this model is given below.

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