Which statement defines best what linear regression attempts to do?

Summarize the values in data

Prove/disprove a hypothesis

Find the best-fitting line through data points

Measure the variation in the data

UnansweredQuestion 2

0 / 6 pts

What does the residual of a point represent in linear regression?

The actual Y - the predicted Y

The intercept of the line

The X value - the Y value

The slope of the line - the intercept

UnansweredQuestion 3

0 / 6 pts

Which best summarizes how the "best-fit line" for data points is generated?

The line with the largest mean residual

The line with the largest square error

The line with the least square errors

The line with the smallest mean residual

UnansweredQuestion 4

0 / 6 pts

Which statement is false about the R^2 of a regression model?

The R^2 measures how much of the variance in the data is accounted for in the model

The R^2 can never go above 1.0

The R^2 measures how much the residuals grow the longer the best-fit line is applied

UnansweredQuestion 5

0 / 6 pts

Ideally, what kind of pattern would we like to see in the residuals in a regression model?

There should be no pattern. The residuals should truly be random

There should be smaller residuals as the actual Y value increases

There should be larger residuals as the actual Y value increases

There should be larger residuals around the median of the actual Y

UnansweredQuestion 6

0 / 6 pts

Among the following, which future value CANNOT be predicted using linear regression on historical data?

Average temperature for a given location

Next number that will be output by a random number generator

Netflix's stock price

Number of iPhones that will be sold

UnansweredQuestion 7

0 / 6 pts

Which statement about the coefficient of determination (R^2) is true?

The coefficient of determination gives an idea about the variation of the dependent variable explained by the model

The coefficient of determination is the square root of the coefficient of correlation

The coefficient of determination gives an idea about the variation of the independent variable explained by the model

The coefficient of determination gives an idea about the overall variation of the dependent variable

UnansweredQuestion 8

0 / 6 pts

Which statement is true about the p-value?

If the p-value associated with a parameter is more than 5%, then this parameter is always considered as significant.

If the p-value associated with a parameter is less than the level of significance, then this parameter is considered as significant.

If the p-value associated with a parameter is less than 5%, then this parameter is always considered as significant.

If the p-value associated with a parameter is more than the level of significance, then this parameter is considered as significant.

Question 9

0 / 6 pts

Which statement is true about the coefficient of correlation?

The coefficient of correlation takes its values from 0 to 1.

The coefficient of correlation indicates the existence of a relationship between two variables.

The coefficient of correlation takes its values from -1 to 1.

A value of -1 of the coefficient of correlation indicates that there is no linear correlation between the considered variables.

Question 10

A multiple linear regression model can have:

One target variable and many dependent variables.

One target variable and many explanatory variables.

One dependent variable and many target variables.

One explanatory variable and many target variables.