Question

Daily Temperatures Number of customers 85 15 90 20 92 13 86 16 88 22 78 30 80 17 83 14 80 20 2. Create the squared term for temperature. 3. Add a qualitative variable to your data set--weekend or weekday (you can call this "Day" for brevity). Code weekdays as 0 and weekends as 1 (if you want to find an effect, you may want to code the busier days as 1, but this is not necessary). 4. Create an interaction between temperature and weekend/weekday. 5. Create an interaction between temperature squared and weekend/weekday. 6. Insert a screenshot of your new data set below.

          Daily Temperatures
Number of customers
85
15
90
20
92
13
86
16
88
22
78
30
80
17
83
14
80
20
2. Create the squared term for temperature.
3. Add a qualitative variable to your data set--weekend or weekday (you
can call this "Day" for brevity). Code weekdays as 0 and weekends as 1
(if you want to find an effect, you may want to code the busier days as 1,
but this is not necessary).
4. Create an interaction between temperature and weekend/weekday.
5. Create an interaction between temperature squared and
weekend/weekday.
6. Insert a screenshot of your new data set below.

Daily Temperatures
Number of customers
85
15
90
20
92
13
86
16
88
22
78
30
80
17
83
14
80
20
2. Create the squared term for temperature.
3. Add a qualitative variable to your data set–weekend or weekday (you
can call this "Day" for brevity). Code weekdays as 0 and weekends as 1
(if you want to find an effect, you may want to code the busier days as 1,
but this is not necessary).
4. Create an interaction between temperature and weekend/weekday.
5. Create an interaction between temperature squared and
weekend/weekday.
6. Insert a screenshot of your new data set below.

Added by Susana G.

Question

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