Genetics: Measure Height Using Height Scale - Assignment Example

The number of male students was 175 while that of females was 244. The data gathered in the initial stage was in raw form then it was copied to excel in two columns, one for male heights while the other was for female heights.

To summarize the data using the Data Analysis ribbon of MS Excel 2007, Descriptive Statistics were calculated. The output is mentioned below. Descriptive Statistics   MALE FEMALE       Mean 179.4685714 165.2828 Standard Error 0.538915079 0.432823 Median 180 165 Standard Deviation 7.12917639 6.760904 Sample Variance 50.82515599 45.70983 Range 39 40 Minimum 162 148 Maximum 201 188 Sum 31407 40329 Count 175 244 Among the given values, the most important are the mean values and the measures of dispersion.

From the table, it is evident that the average male height is 179.5 cm while that of the female is 165.3 cm which shows that on average the male height is greater than the females. The data range is found to be almost similar as it is 39 for males and 40 for females. The standard deviation for male height is 7.13 while that for a female is 6.76 which shows the extent to which an individual data point in the provided sample lies distant from the mean value. Overall the height does not vary to a great extent in both cases as the standard deviation obtained is similar in both cases.

But the observable differences in the mean values of male and female height may be due to the difference in the sizes of each sample. The size of the male height sample is 175 while that of the female height sample is 244 thus both groups differ in their size by 69 units which is a quite significant difference. So to eliminate the impact of this difference on the overall mean values of each sample, the means of each group are required to be tested using statistical procedures. Testing the difference between means Using the Graphpad software, the data were analyzed using an unpaired t-test.

In the given case, the test is employed to test the significance of the difference between the mean values of male and female heights. To perform the statistical test, we need to employ some test statistics that will help in the prediction of the population parameters. Therefore, the test statistics to test the significance of the difference of mean value used is t statistics. The unpaired t-test has been conducted on the given data assuming that both groups have equal variances. Employing a statistical test requires ascertaining some decision rule which in the given case utilizes the P value obtained and is needed to be less than 0.0001. Since the analysis was done using online software, the important values included the P-value, the t-value, the confidence interval, the degree of freedom, and the standard error of the mean (Graphpad Software, Inc.). The output is summarized in the following table.

P-value < 0.0001 T value 20.7036 The confidence interval at 95%  12.84 to 15.53 Degree of freedom 417 Standard error of difference 0.685  The confidence interval is drawn at 95% level, which shows that the mean differences between male and female height varied from 12.84 to 15.53. The obtained difference between the mean heights score between the male and female students is 14.12.