Interpretation of Survey Results

Introduction:

One of the most usual applications of Statistics is describing a set of data using estimation. Given a set of data, for instance, the data analyze using inferential statistics for our survey questions. By analyzing and examining the raw data, we can make and draw logical conclusions or even compare, contrast or rank of this survey or establishments based on the specified questions.

The data picked from survey conducted and provides information about questions asked. It contains information from 54 number of observations and six questions, where a survey responder provided the requested information; it is all self-reported information. There are two types, one is point estimation, and the other is interval estimation (Walpole, 1982). The following are the answers to given questions:

1) Derive logical conclusions from inferential statistical procedures

Many statistics texts pose inferential statistical problems in a disjointed way. By using a simple five-step procedure as a template for statistical inference problems, the student can solve problems in an organized fashion. The problem and its solution will thus be a stand-by-itself organic whole and a single unit of thought and effort.

2) Compute 95% confidence intervals correctly for multiple variables in a study.

The confidence interval for mean value is calculated by formula:

The confidence interval for proportion value is calculated by formula:

Using the excel sheet the 95% confidence interval for all six questions are:

3) Derive appropriate conclusions based upon calculated confidence intervals for a study.

Description:

Question 1: We are 95% confident the true population proportion is between 0.384 and 0.656.

Question 2: We are 95% confident the true population proportion is between 0.384 and 0.656.

Question 3: We are 95% confident the true population proportion is between 0.384 and 0.656.

Question 4: We are 95% confident the true population proportion is between 0.425 and 0.695.

Question 5: We are 95% confident the true population proportion is between 1.921 and 2.259.

Question 6: We are 95% confident the true population proportion is between 1.709 and 2.143.

4) Choose appropriate hypothesis tests based upon the context of the questions asked.

The appropriate hypothesis for each question are given below:

Rules of Rejection null hypothesis:

5) Test statists result:

Decision based on rejection rules or we can reject based on the p value as well. Here we use the rejection rules specified in part 4:

6) Conclusion based on the decision:

1) There is insufficient evidence to conclude that population proportion is less than 0.45.

2) There is sufficient evidence to conclude and support the alternative hypothesis that population proportion is not equal to 0.70

3) There is insufficient evidence to conclude that population proportion is less than 0.55.

4) There is insufficient evidence to conclude that population proportion is greater than 0.60.

5) There is insufficient evidence to conclude and support the alternative hypothesis that the population mean is not greater 2

6) There sufficient evidence to conclude and support the alternative hypothesis that the population mean is not equal to 2.5

References

Walpole, R. (1982). Introduction to Statistics. (3rd ed.). Prentice Hall Publication.

Downie, N. M. & Heath, R. W. (1965). Basic Statistical Methods (2nd ed.). Harper & Row