Question

1. Suppose you run a regression in Excel. What is one way to determine if an explanatory variable is statistically significant?

   		Compare the t-stat with the coefficient
   		Compare the t-stat with the P-value
   		Check if the coefficent is greater than a critical value.
   		Examine the p-value and/or the t-stat.

2. Suppose you wanted to know if there was a relationship between time spent on the internet and IQ. Which model would make the most sense and what would it look like?

		IQ predicting internet, with internet on the left-handed side of the equation and IQ on the right.
		Internet predicting IQ, with IQ on the left-handed side of the equation and internet on the right.
		Internet predicting IQ, with internet on the left-handed side of the equation and IQ on the right.
		IQ predicting internet, with IQ on the left-handed side of the equation and internet on the right.

3. When you run a regression, the computer creates a line of best fit. How is "best fit" measured?

		A line that minimizes the total squared vertical difference between the line and the observation.
		A line that minimizes the total squared horizontal difference between the line and the observation.
		A line that minimizes the total squared diagonal difference between the line and the observation.
		A line that minimizes the squared average of the veritcal and horizontal difference between the line and the observation.

4. Which of the following is not an assumption of a linear regression?

		The variance from the regression line is the same
		The residuals follow a normal distribution.
		The line minimizes the sum of the squared vertical  difference between the observation and the line.
		The slope of the relationship between the X and Y variables is constant.

Answer 1

Suppose you run a regression in Excel. What is one way to determine if an explanatory variable is statistically significant?.

d) Examine the p-value and/or the t-stat.

We use t test for the same

2. Suppose you wanted to know if there was a relationship between time spent on the internet and IQ. Which model would make the most sense and what would it look like?

c) Internet predicting IQ, with internet on the left-handed side of the equation and IQ on the right.

IQ will be the independent variable and time spent on internet is dependent

3. When you run a regression, the computer creates a line of best fit. How is "best fit" measured?

a) A line that minimizes the total squared vertical difference between the line and the observation.

Squared distance between y and y hat

4. Which of the following is not an assumption of a linear regression?

a) The variance from the regression line is the same

This is not the assumption rest are