Question

In: Statistics and Probability

Please Use your keyboard (Don't use handwriting) Thank you.. Courses Name: Introduction to Biostatistics PHC 121...

Please Use your keyboard (Don't use handwriting) Thank you..

Courses Name: Introduction to Biostatistics PHC 121

Please answer the following questions:

***Please i need 500 words ..

I need new and unique answers, please. (Use your own words, don't copy and paste)

Q1. Discuss the tools to measure central tendency?

Q2.

a) Discuss parametric and nonparametric test used for    hypothesis testing.

    b) In a cross sectional study on coronary heart disease (CHD), the smoking and CHD status is summarized below. Use appropriate statistical test to conclude smoking plays any role in CHD.

Smoking

Cardiovascular Diseases

Total

Yes

No

Yes

10

90

100

No

26

74

`100

***Please i need 500 words ..

I need new and unique answers, please. (Use your own words, don't copy and paste)

Solutions

Expert Solution

Q.(1)

Main central tendency measures are mean , median and mode. These three measures show where most of the distributional values fall. Most commonly we use Mean, which is the average of given data. However all three are valid measures of central tendency, we just have to know which measure is appropriate to use where needed. Mean can be applied for both discrete and continuous data. It is computed by adding all observations and dividing it by total number of observations. Important part of mean is that it considers every value in data for calculation. Median is the middle observation of data when data is arranged in increasing order. Median is less affected by outliers. Mode is that value which is most frequent or the one which is highest among all observations. The data can have more than one modes also. It is not very good measure of central tendency.

Q.(2)

(a)

Non parametric tests don't need the data to be normally distributed. However parametric tests are much preferred than non parametric tests. Parametric tests results are more accurate. Statistical power of parametric tests are greater. Non parametric tests use median which are better alternative than mean. Non parametric tests are used when sample is small and non parametric tests can be used for analysis of ordinal data, ranked data and outliers. Some Non parametric tests are Man Whitney Test, Runs Test, Kruskal Wallis Test, Sign Rank Test, Wilkoxon Sign Rank Test, etc. Parametric tests are one and two sample t test, paired t test, z test, f test, etc.


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