Executive Summary

Data for mtcars was extracted from Motor Trend US magazine at 1974 which included 32 automobiles and 10 different designs. In this study we are going to compare effect of automatic and manual transmission on MPG and determination of difference of MPG between automatic and manual automobiles . The results show manual transmission is better than automatic with mean of 17.14737 for Automatic and mean of 24.39231 for Manual.

Exploratory Analysis

      data(mtcars)
       summary(mtcars)

          mpg             cyl             disp             hp             drat             wt       
  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0   Min.   :2.760   Min.   :1.513  
  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5   1st Qu.:3.080   1st Qu.:2.581  
  Median :19.20   Median :6.000   Median :196.3   Median :123.0   Median :3.695   Median :3.325  
  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7   Mean   :3.597   Mean   :3.217  
  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0   3rd Qu.:3.920   3rd Qu.:3.610  
  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0   Max.   :4.930   Max.   :5.424  
            qsec             vs               am              gear            carb      
  Min.   :14.50   Min.   :0.0000   Min.   :0.0000   Min.   :3.000   Min.   :1.000  
  1st Qu.:16.89   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
  Median :17.71   Median :0.0000   Median :0.0000   Median :4.000   Median :2.000  
  Mean   :17.85   Mean   :0.4375   Mean   :0.4062   Mean   :3.688   Mean   :2.812  
  3rd Qu.:18.90   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000 
  Max.   :22.90   Max.   :1.0000   Max.   :1.0000   Max.   :5.000   Max.   :8.000

-Evaluation of MPG according to Transmission:

   boxplot(mpg ~ am, data = mtcars,col  = c("green", "pink"),xlab = "Transmission Type",
   ylab ="Miles / Gallon",main = "MPG by Transmission Type",names= c("Automatic","Manual"),
   horizontal= F)
   

According to plot1 in appendix ;Manual looks better than Automatic beacuse mean of miles per galon in Manual cars is higher than automatics it means that manaual cars can drive longer Miles per gallon, but for evidence based practice it requires hypothesis testing.

-Hypothesis Testing:

H0: Mean MPG for Automatic = Mean MPG for Manual

H1: Mean MPG for Automatic is different to Mean MPG for Manual

     auto=subset(mtcars,select=mpg,am==0)
 manual=subset(mtcars,select=mpg,am==1)
 t.test(auto,manual)
      Welch Two Sample t-test
 data:  auto and manual
t = -3.7671, df = 18.332, p-value = 0.001374
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval: -11.280194  -3.209684
   sample estimates:
   mean of x(Automatic)         mean of y(Manual) 
      17.14737                       24.39231 
      

Results of hypothesis testing reveal Manual transmissions show higher mean of MPG than Automatic therefore amount of distance (Miles) per gallon in manual vehicles is higher than automatic so manual cars can drive longer by certain amount of fuel then Null hypothesis will be rejected and this testing demonstrates that mean of MPG in manual and automatic transmissions are different.

-Regression Analysis:For regression analysis “MPG” defines as Dependent variable and “am” defines as Independient variable

     reg_Mod<- lm(mpg~am,mtcars) 
     summary(reg_Mod)
     Call:
  lm(formula = mpg ~ am, data = mtcars)
  Residuals:
     Min      1Q        Median      3Q     Max 
   -9.3923   -3.0923   -0.2974    3.2439  9.5077 
  Coefficients:
        Estimate        Std.Error    t value     Pr(>|t|)    
  (Intercept)   17.147      1.125      15.247     1.13e-15 ***
    am(Manual)  7.245       1.764      4.106      0.000285 ***
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  Residual standard error: 4.902 on 30 degrees of freedom
  Multiple R-squared:  0.3598,    Adjusted R-squared:  0.3385 
  F-statistic: 16.86 on 1 and 30 DF,  p-value: 0.000285
  

This regression determines Manual is better with average 7.245 miles and R squared id 0.36 with variance of 36% .

-Multivariate Regression:To evaluate effect of other variables on MPG

  reg_total <- lm(mpg~.,mtcars)
  summary(reg_total)
  Call:
  lm(formula = mpg ~ ., data = mtcars)
  Residuals:
    Min      1Q       Median       3Q      Max 
  -3.4506   -1.6044   -0.1196    1.2193    4.6271 
  Coefficients:
            Estimate       Std.Error     t value    Pr(>|t|)  
     (Intercept) 12.30337      18.71788      0.657      0.5181  
  cyl         -0.11144      1.04502      -0.107      0.9161  
  disp         0.01334      0.01786       0.747      0.4635  
  hp          -0.02148      0.02177      -0.987      0.3350  
  drat         0.78711      1.63537       0.481      0.6353  
  wt          -3.71530      1.89441      -1.961      0.0633 .
  qsec         0.82104      0.73084       1.123      0.2739  
  vs           0.31776      2.10451       0.151      0.8814  
  am           2.52023      2.05665       1.225      0.2340  
  gear         0.65541      1.49326       0.439      0.6652  
  carb        -0.19942      0.82875      -0.241      0.8122  
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    Residual standard error: 2.65 on 21 degrees of freedom
   Multiple R-squared:  0.869,   Adjusted R-squared:  0.8066 
   F-statistic: 13.93 on 10 and 21 DF,  p-value: 3.793e-07
   

Evaluation of other variables show although Manual is better but its average reduced to 2.52 miles and R squared shows variance of 86.9% therefore all coefficients are not significant.Then for selection of best variables needs stepwise regression method.

  reg_stepwise=step(reg_total,trace=0)
  summary(reg_stepwise)
  Call:
  lm(formula = mpg ~ wt + qsec + am, data = mtcars)
  Residuals:
   Min      1Q       Median      3Q       Max 
  -3.4811   -1.5555   -0.7257    1.4110    4.6610 
  Coefficients:
               Estimate      Std. Error    t value     Pr(>|t|)    
  (Intercept)   9.6178       6.9596       1.382       0.177915    
  wt           -3.9165       0.7112      -5.507       6.95e-06 ***
  qsec          1.2259       0.2887       4.247       0.000216 ***
  am            2.9358       1.4109       2.081       0.046716 *  
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  Residual standard error: 2.459 on 28 degrees of freedom
  Multiple R-squared:  0.8497,    Adjusted R-squared:  0.8336 
  F-statistic: 52.75 on 3 and 28 DF,  p-value: 1.21e-11
  

Stepwise regression method determines variables such as “wt”,“qsec” and “am” can affect on MPG value more than others , so with variance of 84.9% and coefficients significative of 5% ,the effect of “am” has more significant than “wt” and “qsec” on MPG value. -Analysis of Variance (ANOVA):

  anova(reg_Mod,reg_stepwise,reg_total)
 
  Analysis of Variance Table
   Model 1: mpg ~ am
   Model 2: mpg ~ wt + qsec + am
   Model 3: mpg ~ cyl + disp + hp + drat + wt + qsec + vs + am + gear + carb
      Res.Df    RSS Df Sum of Sq       F    Pr(>F)    
    1     30 720.90                                   
    2     28 169.29  2    551.61 39.2687 8.025e-08 ***
    3     21 147.49  7     21.79  0.4432    0.8636    
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  

ANOVA shows Model 2 with consideration of three variables (“wt”,“qsec”,“am”) is the best choice to evaluate MPG Value.

-Evaluation of Residuals:To evaluate the residuals best model with consideration of three variables (“wt”,“qsec”,“am”) will be plotted

  plot(reg_stepwise, which=c(1:1))
  

-Correlation:

cor(mtcars)[1,]
  
   mpg        cyl       disp         hp        drat           wt        qsec          vs                                                                     
 1.0000000  -0.8521620 -0.8475514  -0.7761684  0.6811719  -0.8676594   0.4186840   0.6640389    

      am         gear           carb
   0.5998324    0.4802848     -0.5509251 
    res_all <- lm(mpg ~ wt+hp+disp+cyl+am, data = mtcars)
par(mfrow = c(2, 2))
 plot(res_all)
 

-Conclusions:According to the analysis of this project ;Manual transmission cars have more miles per gallon in campare to automatic cars but with consideration of other factors such as “wt” MPG will reduced by 2.5 for every 1000 lb increase in weight although increase in “hp” has little effect on MPG but increase in number of cylinders will decrease MPG

Appendix