EconS_311_Lab_Five_Answers[AnnaBrainard]

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Washington State University *

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311

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Statistics

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Jan 9, 2024

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EconS 311 Lab Five Answer Sheet and Check List Name: Anna Brainard Attached Log File (3 points): Attached .do File (2 points): Question 1: If an individual did not answer a closed-ended question (multiple choice or sliding scale questions), the missing data is coded “(.)” which means the questions were left blank. STATA reads it as a number and will include it in statistical analysis. This is helpful to researchers to know what specific values are left blank or missing. Question 2: To “comment” or type a line that STATA doesn’t run, start the line with an asterisk * or begin the comment with *\ and end the comment with \* or if you are commenting at the end of a line of code, start the comment with // Question 3: **histogram of number of W with the frequency on the y-axis W Question 4: the bedrooms coefficient estimate is -70.23759 which means that when there is an increase in 1 bedroom, the value of the residence decreases by 70. 23759. This does not make sense because there are 33 observers and and 29 responded which means there are missing results. Question 5: Yes it does change, for every mile away from the CUB, the coefficient decreases from 429.8886 to 419.04, and the rent decreases 8.6677. Question 6: rent increases by 231.467 when there is a washer and dryer in the unit.

Question 7: (i) gen ResType = (q2 == 4) (ii) tabulate EstRent tabulate Bedrooms tabulate q8 regress EstRent Bedrooms ResType q8 (iii) 10 Question 8: For the variable EstRent, the frequent value of 3 represents the students that pay for about 1080 units. For bedrooms, 4 bedrooms in their place of residency has a frequency of 10 out of the 30 students. For ResType, more students who do not live in apartments answered the survey. Lastly, for q8 when the students ranked the quality of their residencys from 1-5 (1 being the worst, and 5 being perfect) the average was good/average. Question 9: the coefficient of bedrooms is 440.29 units, ResType is -73.69, q8 is -44.918. This means a one unit increase in ResType or Quality leads to a decrease while bedrooms is the only variable where a one unit increase leads to an increase in EstRent. Question 10 : Bedrooms is not statistically significant at the 5% level because the p-value is less then 0.05 so we would reject the null hypothesis. The other variables besides bedrooms you would accept the null hypothesis because they are greater then 0.05 or the 5% statistical significance level.

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