Make sure to include the unit of the values whenever appropriate.

Q1 Build a regression model to predict life expectancy using gdp per capita.

Hint: The variables are available in the gapminder data set from the gapminder package. Note that the data set and package both have the same name, gapminder.

library(tidyverse)
options(scipen=999)

data(gapminder, package="gapminder")
houses_lm <- lm(lifeExp ~gdpPercap,
                data = gapminder)

# View summary of model 1
summary(houses_lm)
## 
## Call:
## lm(formula = lifeExp ~ gdpPercap, data = gapminder)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -82.754  -7.758   2.176   8.225  18.426 
## 
## Coefficients:
##                Estimate  Std. Error t value            Pr(>|t|)    
## (Intercept) 53.95556088  0.31499494  171.29 <0.0000000000000002 ***
## gdpPercap    0.00076488  0.00002579   29.66 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.49 on 1702 degrees of freedom
## Multiple R-squared:  0.3407, Adjusted R-squared:  0.3403 
## F-statistic: 879.6 on 1 and 1702 DF,  p-value: < 0.00000000000000022

Q2 Is the coefficient of gdpPercap statistically significant at 5%?

Hint: Your answer must include a discussion on the p-value. Yes, it is statistically significant because it’s less than 5%. The p value is .0000000000000002 with three stars next to it.

Q3 Interpret the coefficient of gdpPercap.

Hint: Discuss both its sign and magnitude. The coefficient of gdpPercap is estimated life expectancy of 0.00076488. This means that the coeeficient tells us how much the response variable of life expectancy changes per unit

Q4 Interpret the Intercept.

Hint: Provide a technical interpretation. The average life expectancy is 53.95556088 years

Q5 Build another model that predicts life expectancy using gdpPercap, but also controls for another important variable, year.

Hint: This is a model with two explanatory variables. Insert another code chunk below.

library(tidyverse)
options(scipen=999)

data(gapminder, package="gapminder")
houses_lm <- lm(lifeExp ~gdpPercap + year,
                data = gapminder)

# View summary of model 1
summary(houses_lm)
## 
## Call:
## lm(formula = lifeExp ~ gdpPercap + year, data = gapminder)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -67.262  -6.954   1.219   7.759  19.553 
## 
## Coefficients:
##                  Estimate    Std. Error t value            Pr(>|t|)    
## (Intercept) -418.42425945   27.61713769  -15.15 <0.0000000000000002 ***
## gdpPercap      0.00066973    0.00002447   27.37 <0.0000000000000002 ***
## year           0.23898275    0.01397107   17.11 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.694 on 1701 degrees of freedom
## Multiple R-squared:  0.4375, Adjusted R-squared:  0.4368 
## F-statistic: 661.4 on 2 and 1701 DF,  p-value: < 0.00000000000000022

Q6 Which of the two models is better?

Hint: Discuss in terms of both residual standard error and reported adjusted R squared. The modles misses 9.694 years of actual data points. The second model is more acurate because the first model misses 10.49 years. The model is only explaing 43.68 percent life expectancy in years. Actual (.4368)

Q7 Interpret the coefficient of year.

Hint: Discuss both its sign and magnitude. The life expectancy increases by an estimated 0.23898275 years. Per a unit increase 0.01397107 percap. The charts have been dated between 1952-2007.

Q7.a Based on the second model, what is the predicted life expectancy for a country with gdpPercap of $40,000 a year in 1997.

Hint: We had this discussion in class while watching the video at DataCamp, Correlation and Regression in R. The video is titled as “Interpretation of Regression” in Chapter 4: Interpreting Regression Models.

Q8 Hide the messages, but display the code and its results on the webpage.

Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.