# INFERENTIAL STATISTIC

**Topics:**Statistical hypothesis testing, Statistical inference, Standard deviation

**Pages:**7 (541 words)

**Published:**October 12, 2014

Inferential Statistics and Findings

Erick Mart

QNT/561

August 25th 2014

Mario LOPEZ

Inferential Statistics and Findings

Inferential Statistic is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation. Our team uses inferential statistic to compare two groups, which are Melks and DHL. This paper outlines the sampling and data collection procedure used to test the null hypothesis. The null and alternate hypotheses are: (There is no significant difference in brand awareness based on the marketing channel used). (There is a significant difference in brand awareness on the basis of the marketing channel used). Here is an example of the statistics of our results describing the total number of people from minimum age to maximum from ages 35 to 55. Mock data for the independent variables for Melks.

Descriptive statistics

Income

Age

Count

300

300

Mean

56,426.45

45.91

sample standard deviation

3,876.30

7.23

sample variance

15,025,706.87

52.29

Minimum

50000

34

Maximum

60000

55

Range

10000

21

confidence interval 95.% lower

54,135.75

41.64

confidence interval 95.% upper

58,717.16

50.18

half-width

2,290.71

4.27

z

1.96

1.96

confidence interval 95.% lower

53,822.32

41.05

confidence interval 95.% upper

59,030.59

50.77

half-width

2,604.13

4.86

t(df = 10)

2.228

2.228

1st quartile

54,509.00

41.00

Median

57,034.00

48.00

3rd quartile

59,605.50

50.50

interquartile range

5,096.50

9.50

The Pie chart below states the percentages of income of each region surveyed, starting with Los Angeles leading with 44%, New York with 35%, and the southern region with 21%. Los Angeles and New York combined holds nearly 80% of the income documented in the surveys.

The next pie graphs explain how MELKS services where utilized from consumers by ordering merchandise online from Online stores like Amazon, eBay, Craig’s list, and a cluster of department stores while and receiving by Melks carriers. Also one of the graphs show the percentage DHL controls with their deliveries from these same online stores. Although the graphs look very similar, however they are different in the number of customers of whom use the services.

The above column chart shows how we picked the targeted group for our team study with the people in the 35-55 years old age group. These particular groups of people have families, and they use delivery services of some type when ordering, delivering or purchasing products through the Internet. In conclusion Inferential Statistics is drawing conclusions from data that are subject to random variation in this case is Melks and DHL and this shows us the difference in percentage of usage between the two carrier services Melks and DHL. This has give us more information to determine if the null hypothesis will be correct or if we will need to accept the alternative hypothesis.

REFERENCE

Heppner, P. P., Kivlighan, D. M., Jr., & Wampold, B. E. (1999). Research design in counseling (2nd ed.). New York: Brooks/Cole. Kerlinger, F. N. (1986). Foundations of behavioral research (3rd ed.). Fort Worth: Holt, Rinehart and Winston, Inc.

Smith, Ph.D., S. (2013). Determining Sample Size: How to Ensure You Get the Correct Sample Size. Retrieved from...

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