glm() Practice: Text Ban

This question is essentially the same as one of Stat 200's HW problems.

A total of 618 students responded to a Stat 100 survey in Fall 2009. Three of the questions asked were:

1. About how many times do you text per hour of driving on the average?
2. Do you think there should be a law against texting while driving? (0=No, 1=Yes)
3. Are you male or female? (0=Male, 1=Female)

Instead of using the whole data of 618 students, 580 students are chosen randomly from the survey data by the computer. Copy and paste the following code to your R console. These are the subset of data chosen by the computer.

# Text ban? 1=yes; 0=no
text_ban <- c(1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0)

# gender: 0=male; 1=female
Gender <- c(1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1)

# Number of texts per hour driving
texts <- c(10, 0, 60, 15, 4, 0, 20, 20, 4, 0, 12, 2, 5, 1, 2, 1, 1, 4, 10, 1, 0, 4, 6, 3, 1, 2, 1, 0, 1, 5, 3, 1, 1, 10, 0, 5, 0, 1, 1, 5, 4, 2, 1, 2, 2, 3, 3, 60, 6, 30, 0, 5, 6, 1, 5, 2, 0, 4, 4, 0, 0, 1, 2, 3, 1, 1, 6, 2, 10, 1, 1, 1, 1, 9, 1, 0, 1, 1, 17, 30, 1, 4, 5, 2, 1, 4, 5, 1, 6, 4, 2, 7, 2, 3, 10, 1, 2, 3, 10, 5, 10, 5, 5, 1, 0, 20, 1, 10, 0, 12, 1, 1, 1, 0, 5, 6, 10, 3, 10, 1, 0, 2, 0, 0, 0, 10, 2, 2, 3, 3, 1, 15, 1, 0, 45, 2, 8, 1, 2, 10, 1, 4, 1, 0, 3, 10, 5, 5, 3, 20, 1, 8, 1, 30, 2, 10, 0, 2, 1, 10, 2, 3, 0, 0, 6, 0, 1, 3, 0, 1, 0, 3, 2, 3, 1, 2, 1, 1, 1, 0, 1, 0, 24, 2, 10, 8, 1, 5, 2, 1, 10, 0, 0, 5, 2, 4, 10, 20, 5, 15, 12, 5, 4, 20, 3, 5, 1, 4, 2, 2, 1, 5, 0, 3, 1, 52, 1, 2, 10, 2, 5, 10, 3, 2, 0, 20, 10, 15, 1, 2, 3, 1, 14, 3, 40, 0, 0, 1, 2, 1, 2, 4, 25, 4, 0, 25, 1, 5, 3, 6, 3, 6, 0, 4, 10, 5, 10, 20, 13, 0, 20, 15, 0, 1, 2, 10, 6, 10, 0, 0, 20, 10, 4, 4, 2, 2, 5, 3, 1, 2, 0, 3, 0, 0, 3, 4, 1, 3, 50, 3, 1, 0, 6, 4, 7, 8, 0, 2, 1, 3, 2, 0, 1, 2, 0, 2, 0, 1, 2, 3, 0, 3, 10, 5, 0, 5, 1, 3, 0, 6, 15, 7, 3, 20, 3, 27, 3, 2, 0, 10, 5, 4, 4, 0, 0, 0, 1, 0, 0, 5, 5, 4, 10, 3, 1, 10, 3, 10, 10, 10, 0, 3, 2, 10, 1, 25, 3, 0, 0, 5, 9, 2, 14, 3, 1, 0, 1, 1, 1, 5, 27, 0, 2, 0, 0, 10, 5, 3, 17, 3, 3, 25, 25, 3, 10, 2, 10, 1, 10, 6, 5, 2, 5, 0, 5, 0, 2, 3, 3, 0, 10, 1, 3, 0, 2, 0, 3, 2, 0, 0, 20, 5, 10, 1, 7, 1, 6, 2, 1, 2, 1, 0, 5, 0, 1, 1, 5, 5, 1, 10, 25, 0, 1, 0, 10, 20, 6, 3, 8, 0, 0, 3, 0, 2, 5, 10, 7, 0, 0, 2, 3, 1, 5, 6, 4, 0, 8, 4, 2, 1, 8, 0, 0, 26, 2, 1, 2, 5, 0, 20, 6, 0, 5, 4, 8, 0, 5, 2, 5, 10, 22, 2, 20, 10, 0, 3, 4, 1, 0, 0, 1, 1, 2, 4, 20, 1, 4, 5, 1, 3, 26, 2, 1, 60, 4, 6, 0, 10, 8, 1, 2, 0, 1, 1, 25, 0, 5, 0, 40, 1, 3, 3, 60, 0, 0, 4, 1, 2, 20, 1, 15, 1, 2, 1, 10, 4, 3, 0, 4, 3, 1, 0, 2, 1, 10, 0, 22, 3, 3, 5, 4, 15, 1, 15, 0, 0, 3, 30, 0, 0, 15, 3, 0, 5, 2, 2, 1, 10, 7, 16, 3, 20, 2, 10, 4, 2, 18, 1, 4, 2)

a. Fit a logistic regression model predicting 'text ban' from Gender and number of texts per hours. Fill in the following table below and give your answers to 4 significant figures.

b. Are females more or less likely to be for a text ban than males given the same texting frequency?
Same
Not enought information
Less
More

c. The more texts per hour the ___________ the probability of being for a text ban given the same sex.
not enought information
lower
same
higher

d. Use the predict() function to calculate probability of being for a text ban for the individuals in the table below: