remove shiny app from reg-table guide

reg-table/reg-table.Rmd

@@ -24,11 +24,7 @@ Regression is a method for calculating the line of best fit. The regression line
 
 Independent and dependent variables have many synonyms, so it helps to be familiar with them. They are the explanatory and response variables, input and output variables, right hand side and left hand side variables, explanans and explanandum, regressor and regressand, predictor and criterion variable, among many others. The first thing you need to do when you see a regression table is to figure out what the dependent variable is---this is often written at the top of the column. Afterwards identify the most important independent variables. You will base your interpretation on these.
 
-A positive relationship in a regression means that high values of the independent variable are associated with high values of the dependent variable. A negative relationship means that units which have high values on the independent variable tend to have low values on the dependent variable, and vice versa. Regressions can be run to estimate or test many different relationships. You might run a regression to predict how much more money people earn on average for every additional year of education, or to predict the likelihood of success based on hours practiced in a given sport.
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-Use the app below to get a feel for what a regression is and what it does. Below we will talk through the output of the regression table. Fill in values for x and for y and then look to see how the line of best fit changes to capture the average relationship between x and y. As the line changes, so too does the key information in the regression table.
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-<iframe height="500" src="https://egap.shinyapps.io/Regression101/" width="850"></iframe>
+A positive relationship in a regression means that high values of the independent variable are associated with high values of the dependent variable. A negative relationship means that units which have high values on the independent variable tend to have low values on the dependent variable, and vice versa. Regressions can be run to estimate or test many different relationships. You might run a regression to predict how much more money people earn on average for every additional year of education, or to predict the likelihood of success based on hours practiced in a given sport. Below we will talk through the output of the regression table.
 
 2 What is a regression equation?
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