While Microsoft Excel is generally not the preferred method for completing statistical analyses in Public Health research, it is essential for data management and is useful for preliminary statistical analyses. For any public health job you will be expected to be proficient in the use of this program. For this assignment you will be using Excel to analyze the data shown in the table below. These data represent weight (in kilograms) of third grade students from a public elementary school in a rural town and an elementary school in an urban town.

Weight of Children in Third Grade (kg)
Rural School	Urban School
Girls	Boys	Girls	Boys
26	19	39	25
28	21	35	29
19	26	41	33
25	27	30	48
32	28	26	40
22	23	24	41
29	25	26	32
30	22	36	28
28	24	30	29
35	19	27	23
21	26	26	30
36	28	30	28
18	20	38	25
25	25	33	38
31	18	29	36

Descriptive Statistics

Provide a table that includes Mean, Median, Mode, Range and Standard Deviation for each of the four student populations

Paste your Descriptive Statistics table here:

Descriptive data is often represented visually, most commonly with a histogram. Provide a histogram that represents each of the four data sets

Paste your Histograms here:

Inferential Statistics - comparing groups

t- tests: Since you have already calculated the mean and standard deviation for each of your four populations, the simplest way to accomplish a t-test is by using anonline t-test calculator.

For this particular t-test calculator you will:

1. Choose your data entry format -i.e. Enter mean, SD, and N
2. Choose your test (unpaired for paired t-test)
3. Enter your data
4. Click calculate

Provide a table of P values for each of the following t-test analyses.

• Compare weights of boys from the urban school to the weights of boys from the rural school.
• Compare weights of girls from the urban school to the weights of girls from the rural school.
• Compare weights of boys from the urban school to the weights of girls from the urban school.
• Compare weights of boys from the rural school to the weights ofgirls from the rural school.

Paste your table with P values here:

How would you interpret these statistical analyses? What conclusions would you draw?

ANOVA:If you want to compare the means of all four of your groups simultaneously provide an ANOVA analysis. Again, since you have already used Excel to calculate the mean and standard deviation you can use anonline ANOVA calculator.

When you enter your data (Mean, SD, N) for each group and click calculate, the program will calculate the ANOVA test statistics, including the P value. This P value tells you if there are any statistical differences between the means of your groups. It is important to recognize that this analysis does not tell you which means are statistically different. When the results of an ANOVA analysis indicate statistical difference, you may want to do additional statistical analyses to find outwhich populationmeans are different. Show an ANOVA of the weights of the four populations from the data set of weights among third grade students and report the P value.

Paste your ANOVA P value here:

How would you interpret these statistical analyses? What conclusions would you draw?

Inferential Statistics - associations between variables

For this analysis you will look at the association between the number of hours students sleep each night and their grade point average.

Pearson Correlation:

Using Excel, calculate the correlation coefficient (r value) for the data in the table below. You can use thisUsing Excel to calculate a correlation coefficient || interpret relationship between variables video as a reference.

Hours of Sleep	GPA
9	3.8
7	2.9
8	3.5
9	3
6	2.6
8	3.7
8	3.9
7	3
9	3.8
8	2.9
6	2.6
7	2.4
8	2.9
10	3.2
6	3
8	3.7
9	3.5
7	3
9	3.6
7	2.2

Once you have calculated your correlation coefficient, you can draw some conclusions about your data - for example, you can determine if there is a positive or negative relationship between the variables, and if the relationship is weak, moderate or strong. However, you do not know if the relationship is statistically significant until you calculate significance (P value).

Pearson's Correlation coefficient:

What conclusions can you draw from your calculated correlation coefficient?

How would you interpret these statisticalanalyses? What conclusions would you draw?