The Implementation of Applied Statistics in the Car Manufacturing Industry

Applied statistics is the practice of using various statistical methods and techniques to define and solve business problems. As companies get access to big data day in day out, they are constantly looking for data analysts, data scientists, statisticians, and other professionals who are well versed in applied statistics to visualize and analyze data, draw inferences from it, and use it to find solutions to real-world problems. Businesses have plenty of data and when it is properly analyzed, there are higher chances of increasing efficiency and profitability.

Descriptive statistics

We have a Chosen dataset of cars manufactured in the US, Europe, and Japan with the variables of interest miles per gallon, Origin of the car(Categorical),Acceleration of Car, Horsepower of car and weight of the car, and Type of cylinder(Categorical).
The type of cylinder is coded as high for 8 cylinder cars, medium for 6 cylinder cars, and low for cylinders less than 6.

Graphs and Descriptive Statistics

From this box plot of Acceleration of cars categorized by different origins, we can Median Acceleration is more for Japan than Europe than the US. But Acceleration has more variation across cars in Europe than in the US than in Japan.

From the Scatterplot of the weight of car and Horsepower of car, we can see a trend that the Horsepower of the car increases with an increase in weight of the car.

From this box plot of Horsepower of cars categorized by different origins, we can Median Horsepower is more for the US than Europe than Japan. But Horsepower has more variation across cars in the US than in Japan than in Europe.

From the Scatterplot of miles per gallon of car and Horsepower of car, we can see a trend that Miles per gallon of the car decreases with an increase in Horsepower of car.

Mean of acceleration
Europe Japan US
16.8219 16.17215 14.94252
the standard deviation of acceleration
Europe Japan US
3.01092 1.954937 2.804542
Frequency Table between Origin and Cylinder type in cars
Europe Japan US
high 0 0 108
low 69 73 72
medium 4 6 74
Mean of Horsepower
Europe Japan US
78.78082 79.83544 118.0118
the standard deviation of Horsepower
Europe Japan US
24.4627 17.8192 42.39793
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Hypothesis Testing

Null Hypothesis: Mean acceleration for cars is the same across cars of all origins

Alternate Hypothesis: Mean acceleration is different for cars of at-least one origin than others. Single-factor ANOVA Result

ANOVA Table Origin and Acceleration
Df Sum Sq Mean Sq F-value P-value
Origin 2 242 121 16.58 0.00E+00
Residuals 403 2941 7.3
Conclusion-Since p-value is less than 0.05 we can reject the Null hypothesis at a significance level of 0.05 and conclude that we have significant evidence that Mean acceleration is different for cars of at-least one origin than others.

Null Hypothesis: Origin of car and type of Cylinder are independent of each other. Alternate Hypothesis: Origin of car and type of Cylinder are not independent of each other. Chi-Square test of independence between categorical variables.

Pearson's Chi-squared test
X-squared = 164.52 df = 4  p-value =0
Conclusion-Since the p-value is less than 0.05 we can reject the Null hypothesis at a significance level of 0.05 and conclude that we have significant evidence that the Origin of the car and type of Cylinder is not independent of each other.

Null Hypothesis: There is no relationship between the weight of a car and horsepower.i.e correlation coefficient is 0.

Alternate Hypothesis:There is a relationship between the weight of a car and horsepower.The correlation coefficient is different from 0.

      correlation between weight and Horsepower
0.8408106
t-test for correlation
t = 31.22 df = 404  p-value =0
Conclusion-Since the p-value is less than 0.05 we can reject the Null hypothesis at a significance level of 0.05 and conclude that we have significant evidence that there is a relationship between the weight of a car and horsepower. That meansthe correlation coefficient is significantly different from 0. Null Hypothesis: There is no relationship between Miles per gallon and horsepower .i.e correlation coefficient is 0. Alternate Hypothesis: There is a relationship between Miles per gallon and horsepower.The correlation coefficient is different from 0.
      correlation between Miles per gallonand Horsepower
-0.7267
t-test for correlation
t = -21.261 df = 404  p-value =0
Conclusion-Since p-value is less than 0.05 we can reject the Null hypothesis at a significance level of 0.05 and conclude that we have significant evidence that there is a relationship between Miles per gallon and horsepower. That meansthe correlation coefficient is significantly different from 0.

Null Hypothesis: Mean Horsepower for cars is the same across cars of all origins Alternate Hypothesis: Mean Horsepower is different for cars of at-least one origin than others. Single-factor ANOVA Result

ANOVA Table for Origin and Horsepower
Df Sum Sq Mean Sum Sq F P-value
Origin 2 142337 71168 54.88 0
Residuals 403 522642 1297
Conclusion-Since p-value is less than 0.05 we can reject the Null hypothesis at a significance level of 0.05 and conclude that we have significant evidence that Mean Horsepower is different for cars of at-least one origin than others. To attain high grades in papers derived from this topic, take our hypothesis testing assignment help.