Editing Statistics and Statistical Programming (Spring 2019)/Problem Set: Week 8
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: '''PC1.''' Refamiliarize yourself with the data and recode your variables as you did for [[Statistics and Statistical Programming (Spring 2019)/Problem Set: Week 3|Week 3 PC8]]. You may recall from that x and y looked like they might be related. We now have the tools and terminology to describe this relationship and to estimate just how related they are. | : '''PC1.''' Refamiliarize yourself with the data and recode your variables as you did for [[Statistics and Statistical Programming (Spring 2019)/Problem Set: Week 3|Week 3 PC8]]. You may recall from that x and y looked like they might be related. We now have the tools and terminology to describe this relationship and to estimate just how related they are. | ||
: '''PC2.''' Run a t.test between x and y in the dataset and be prepared to interpret the results. | : '''PC2.''' Run a t.test between x and y in the dataset and be prepared to interpret the results. | ||
: ''' | : '''PC23''' Estimate how correlated x and y are with each other. | ||
: '''PC4.''' Fit a linear model corresponding to the following formula and be ready to interpret the coefficients, standard errors, t-statistics, p-values, and <math>\mathrm{R}^2</math> of it: Β | : '''PC4.''' Fit a linear model corresponding to the following formula and be ready to interpret the coefficients, standard errors, t-statistics, p-values, and <math>\mathrm{R}^2</math> of it: Β | ||
:: <math>\hat{y} = \beta_0 + \beta_1 x + \varepsilon</math> | :: <math>\hat{y} = \beta_0 + \beta_1 x + \varepsilon</math> |