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The standard linear regression assumptions issues

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Reference no: EM13800381

Questions

Suppose we only want to consider using the page views of one cryptocurrency (CC) to predict the page views of the phrase, Alternative currency (alt_cur). Which CC would be the worst choice to make predictions?

Does this CC (the answer to question 1) significantly predict alt_cur?

Now, consider the variable which best predictsalt_cur. Call it CCbest. What is the residual standard error associated with the regression of alt_cur and CCbest?

Plot CCbest against the residuals from the regression of alt_cur on CCbest. Do the residuals appear to be approximately normally distributed?

Run a regression predicting alt_cur from litecoin. What percent of the total variation in alt_cur can be explained by litecoin? Don't include the percent sign but remember to round to two decimals.

Plot Date versus the residuals of the regression from question 5. Do the residuals follow the standard linear regression assumptions?

In what month do you find the most extreme residual? Don't report the associated year.Answer in lowercase.

Which (if any) CC should not be used to predict alt_cur in a linear model due to statistical insignificance? Choose one of bitcoin, dogecoin, litecoin or none.

Which CC is least correlated with the other two CCs? If all are equally correlated, write none.

Calculate a new variable with the command, bit_rate<- 24*60^2/bitcoin.

Reference no: EM13800381

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