Midterm essay questions

Midterm Essay questions

Q.1

It is a natural phenomenon that a body reduced its weight it is exercised. So, the relationship between exercise and weight loss is always positive. The more the body is exercised, the more body is reduced. To prove this relationship, 40 people were monitored during their exercise for a month and their weight loss was measured. Following is the data:

No. of hours of exercise * Weight loss (Kg) Cross tabulation

count

Weight loss (Kg)

Total

1

2

3

4

5

8

9

No. of hours of exercise

1

4

4

5

1

1

0

0

15

2

1

2

1

1

2

0

0

7

3

0

1

2

2

3

0

0

8

4

0

0

1

3

3

2

1

10

Total

5

7

9

7

9

2

1

40

The results were a little deviated because weight loss varies from person to person. Sometimes, it happened that more exercise results in a less weight loss and sometimes less exercise results in a more weight loss. Following are the results obtained

Descriptive Statistics

Mean

Std. Deviation

N

No. of hours of exercise

2.3250

1.22762

40

Weight loss (Kg)

3.6000

1.90546

40

Correlations

VAR00001

VAR00002

No. of hours of exercise

Pearson Correlation

1

.638**

Sig. (2-tailed)

.000

N

40

40

Weight loss (Kg)

Pearson Correlation

.638**

1

Sig. (2-tailed)

.000

N

40

40

**. Correlation is significant at the 0.01 level (2-tailed).

Analyzing the results

The correlation between the two variables is found out to be .638, i.e. both the variables are explaining 63.8% part of each other. Practically, this is not a good correlation but let us consider in mind that the variables which we have taken here are both human dependent and the variability in a human is extremely unpredictable. So, the results can be concluded as satisfactory (Lyman Ott & Michael Longnecker, 2010).

Q.2

Probability Sampling

In probability sampling method there is a utilization of some forms of random selection. In random selection method, it is must set up some procedure or process that assures probability of different samples being chosen is always equal i.e. no sample has a greater chance of being chosen (Macmillan, 1968).

Example- Simple Random Sampling: There are 100 balls in a basket. When someone picks a ball from the basket with looking at it randomly, this selection is called simple random sampling where every ball has equal chances to be selected.

Non-Probability Sampling

The sampling in which some pre-defined work is being done without depending chances of any variable to occur i.e. every sample has a surety of being done because it is done manually.

Example- Purposive Sampling: When some sampling is done for a known purpose in which every sample has a surety of being right and could not vary. A survey for liking a TV program in a shopping has no probability involved in it as every survey has its complete report without any chances that a person will like the program or not (Macmillan, 1968).

Sampling a population using Probability Distribution

The sample of a population for a probability distribution can be taken as a group of university students taking part in a singing competition. Now, Simple random sampling method is the best to be implemented here. As university has more than 2000 students, so it will be extremely difficult to call all of them audition. Therefore, a small sample of 5-10 students of every class will be selected randomly and a very small no. of students say 100 would be called for audition.

Sampling a population using Non-Probability Distribution

A company is trying to ...