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Stat1300 Fundamentals Of Statistics For Assessment Answers

Discuss about the Fundamentals of Statistics For Results and Data Analysis. 

Answer:

Introduction

Australia being one of the countries where cars are produced, it is in our expectation that most of the car brands spotted around the cities and towns within the country should be local made vehicles. This does not hinder or nullify the fact that other foreign brands were spotted, but the larger proportion of the cars’ population in the country were expected to be local made brands such as Ford, Holden, Toyota, Nissan etc. with this idea in mind therefore, observations were made across the major points of roads intersection (i.e. Verve Bar, Moore Park and Carlingford) that formed major traffic circles in three major streets in the city of Sydney where the brands of cars were recorded in different three time intervals (i.e. 8:00 am to 8:30 am, 12:30 pm to 1:00 pm and lastly 5:00 to 5:30 pm). The frequency of the car brands as recorded from the observation were therefore expected to be used in the comparison for clarity of the pre-formed conclusion by our expectations.

Results, Data Analysis and Discussion of Results

Table 1: Origin of Car Brands

 

Frequency

Percent

Valid Percent

Cumulative Percent

Australia

43

62.3

62.3

62.3

Foreign

26

37.7

37.7

100.0

Total

69

100.0

100.0

 

As recorded in the table above, a larger percentage of the cars that were spotted at the time of observation in the intersection road points in the city of Sydney represented by 62.3% were the Australian local made cars compared to 37.7% that represented the foreign cars that were imported in the country.

From the collected data, Holden being one of the local made car brands in Australia, it was represented by 24.6% of the observed cars, Jaguar a foreign car brand was represented by 5.8%, Toyota another local made brand was represented by 26.1%, Honda was represented by 2.9% and Nissan was represented by 8.7% of the observed car brands though they were as well the local made brands. Other foreign car brands such as Subaru was represented by 7.2%, Hyundai 5.8%, Lexus 8.7%, BMW 4.3% and finally Mercedes Benz 5.8%.

Table 2: Car brand * Origin Crosstabulation

 

Origin

Total

Australia

Foreign

Car_brand

Holden

Count

17

0

17

% within Car_brand

100.0%

0.0%

100.0%

Jaguar

Count

0

4

4

% within Car_brand

0.0%

100.0%

100.0%

Toyota

Count

18

0

18

% within Car_brand

100.0%

0.0%

100.0%

Honda

Count

2

0

2

% within Car_brand

100.0%

0.0%

100.0%

Nissan

Count

6

0

6

% within Car_brand

100.0%

0.0%

100.0%

Subaru

Count

0

5

5

% within Car_brand

0.0%

100.0%

100.0%

Hyundai

Count

0

4

4

% within Car_brand

0.0%

100.0%

100.0%

Lexus

Count

0

6

6

% within Car_brand

0.0%

100.0%

100.0%

BMW

Count

0

3

3

% within Car_brand

0.0%

100.0%

100.0%

Mercedes-Benz

Count

0

4

4

% within Car_brand

0.0%

100.0%

100.0%

Total

Count

43

26

69

% within Car_brand

62.3%

37.7%

100.0%

The above contingency table was used to compare for the association between car brands and the origin. The Chi- square test was thereafter conducted to determine the association between the two variables and the results of the test were as displayed in the chi square table 3 below.

Table 3: Chi-Square Tests

 

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

69.000a

9

.000

Likelihood Ratio

91.422

9

.000

N of Valid Cases

69

 

 

a. 16 cells (80.0%) have expected count less than 5. The minimum expected count is .75.

The significance values for the test being that it was less than the p-value i.e. (0.05) for the Pearson Chi-Square, it therefore confirmed that there indeed existed an association between the car brand and the origin of the cars since the test was statistically significant. Considering the percentage of the number of expected counts less than 5, the percentage is greater than 20% hence could lead to otherwise conclusion that would be different from this made conclusion.

Table 4: Symmetric Measures

 

Value

Approx. Sig.

Nominal by Nominal

Phi

1.000

.000

Cramer's V

1.000

.000

N of Valid Cases

69

 

a. Not assuming the null hypothesis.

b. Using the asymptotic standard error assuming the null hypothesis.

Cramer’s V was used in order to test for the strength of association of car brand and car origin which further confirmed that there was strong association between the two variables as the strength value displayed was (1.000). 

Discussion of the results

From the observations that were made, the results revealed that the local made car brands were many on the streets of city of Sydney compared to foreign or imported car brands since the Australian cars formed 62.3% of the observations made. This therefore led to answer the question that there were more Australian made cars on roads in the city than foreign made cars. Specific Australian made cars that were common on the roads were Toyota and Holden represented by 26.1% and 24.6% respectively. Foreign products are available or imported in Australia as a result of free trade agreement with other countries which liberalizes access to Australian market for goods and services and also investments, this is according to (Miller et al, 2015). The free trade agreements also aimed at protecting the local products as confirmed by the dominance of the local made cars on the roads. As well, it also confirmed why foreign cars could be spotted on the roads in a substantial percentage of 37.3%. According to (Arminger et al, 2013), contingency tables are used to check for association between categorical variables. It was therefore used to test for association between car brands and origin which were then found to be strongly associated.

Conclusion

It can therefore be concluded from the results that most of the cars that were seen on roads

on the streets in city of Sydney were Australian made cars which responds to the hypothesis of there being more Australian made cars than the foreign cars.  

References

Miller, T., Kim, A. B., & Holmes, K. (2015). 2015 Index of economic Freedom.Washington DC: The Heritage Foundation.

Arminger, G., Clogg, C. C., & Sobel, M. E. (Eds.). (2013). Handbook of statistical modeling for the social and behavioral sciences. Springer Science & Business Media.


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