Question

Instructions:

1. Come up with two example data sets of your own whose standard deviations would be interesting to compare. Some examples:

   a) Potato weights vs onion weights.

   b) Female heights vs male heights

   c) National league batting averages vs American league batting averages

An example that doesn't work: GPAs vs SATs. These are two different variables that even use different units. So comparing their standard deviations is meaningless. However, male GPA vs female GPA would be a valid comparison.

2. Get sample data for the two data sets you chose by measuring, surveying, researching, etc. Sample sizes must be at least 10, but the more the better.

3. Compute the means, standard deviations and variances for the two data sets.

4. Compute the z-score and percentile for two values from each data set (for a total of four z-scores and four percentiles).

Help!

Answer 1

Std Dev =

Z-score =

Dataset 1

SL.no	Male Height	Female Height
1	174	161.8
2	174.6	159.6
3	175.6	161.01
4	177.8	158.1
5	179	161.8
6	180	163.8
7	178.8	166
8	179.2	167
9	171.8	167.6
10	165.1	165.4
11	171	154.2
12	178.7	156.6
13	178.6	150.6
14	183.9	168.1
Total	2468.1	2261.61
Average	176.2929	161.5436
Std Dev	4.716169	5.287456

Z-score for male height 171 = -1.223 , percentile = P(Z) = 11.067%

Z score for female height 154.2 = -1.388, percentile = P(Z) = 8.25%

Datase-2

	Economic Test Scores
SL.no	Male	Female
	59.7	59
	60.8	50.3
	68.4	49.2
	58.2	57.5
	61	55.1
	62.8	69.5
	58.8	67.8
	58.8	59.3
	54.8	57.5
	65	62.4
	62.3	61.2
	64.3	51.5
Total	734.9	700.3
Average	61.24167	58.35833
Std Dev	3.61272	6.374161

Zscore for male score 65 = 1.040 , percentile = P(Z) = 85.08%

Zscore for female score 65 = 1.042 , percentile = P(Z) = 85.13%