Hello, I have a statistical report due and I did a rough draft that the professor gave me feedback on. Could you provide any help with the conclusion and pointers on a better flow? It's some what long I'm just needing any other type of feed back or suggestionon the conclusion. Thanks

Feed back received from my professor was" Looks like you have all of the components here. I like your assumptions section. I think you just need some more text to improve the reading flow. Also, please summarize the whole study with a conclusion"

I do have charts and graphs on my paper however I could not add them

Paper as follows

The purpose of this statistical report is to analyze the unemployment rate in North Carolina compared to Texas for the 2019.

Summary

The purpose of this statistical report is to analyze the unemployment rate in North Carolina fo the year of 2019 compared to the unemployment rate in Texas in 2019. In this report we will accumulate reliable data from online sources and compare the unemployment rates of two states. With the results of this study,we will conclude which unemployment rate is higher in 2019.This report contains the following: an explanation of the study, the method by which the samples were selected from the population and the chosen sample size,the data, the statistical methodology, and a summary of my results.

Description of the Study

Unemployment has plagued many states, some states worse than other in recent years. For the states of North Carolina and Texas, how the unemployment rate is calculated is essential in first being able to understand the data that will be presented. The unemployment rate is defined as the proportion of the nation's non-institutionalized population sixteen years and older that is out of work, actively looking for a job, and available for work (Frumkin, 1998). Institutionalized people confined to facilities such as nursing homes or jails are not included in the rate. U.S. armed forces members are also excluded so that the measure represents only the civilian labor force (Frumkin, 1998). The purpose of the study is to check the unemployment rate in North Carolina compared to Texas for 2019. To compare the difference between unemployment rate in NC, and Texas, the t test is appropriate.

Mean of NC % is 3.875

Mean of TX % is 3.5

The data and the means of collection

To determine the outcome for the unemployment rates, data was collected from The Local Area Unemployment Statistics (LAUS) program a federal-state cooperative effort between the North Carolina Department of Commerce, Labor and Economic Analysis Division (LEAD),the U.S. Department of Labor's Bureau of Labor Statistics (BLS) and Home Facts. The Data was collected for the months of 2019 and contains unemployment rates in North Carolina and Texas percentages.

The DATA below is placed in excel

Data Below

Month/Year NC % National % Jan-19 4.50% 4.00% Feb-19 4.20% 3.80% Mar-19 4.10% 3.80% Apr-19 3.50% 3.60% May-19 3.90% 3.60% Jun-19 4.20% 3.70% Jul-19 4.30% 3.60% Aug-19 4.10% 3.70% Sep-19 3.40% 3.50% Oct-19 3.50% 3.60% Nov-19 3.50% 3.50% Dec-19 3.30% 3.50% Texas: Month/Year TX % National % Jan-19 4.10% 4.00% Feb-19 3.70% 3.80% Mar-19 3.50% 3.80% Apr-19 3.00% 3.60% May-19 3.10% 3.60% Jun-19 3.70% 3.70% Jul-19 3.80% 3.60% Aug-19 3.70% 3.70% Sep-19 3.40% 3.50% Oct-19 3.30% 3.60% Nov-19 3.40% 3.50% Dec-19 3.30% 3.50%

The statistical methodology used for analysis of the data

The standard deviation of NC is 0.4414.

The standard deviation of TX is 0.3133.

There is less variation in the TX unemployment rate as compared to NC unemployment rate.

The negative value of the kurtosis indicates the distribution of NC and TX is flat.

NC is positively skewed, and TX is negatively skewed.

The t test will be used to compare the mean difference in unemployment rates between TX and NC.

The Problem Statement:

The purpose of this statistical report is to analyze the unemployment rate in North Carolina compared to Texas for 2019.

The Solution Data Inputs and Outputs:

Starting with performing the t test. Here it is assumed that the standard deviation for both groups is unknown and equal.

Hypotheses for the text are

Ho: The unemployment rate in NC and TX is the same

H1: The unemployment rate is NC and TX is not the same

The Data is entered into excel as followed an T sample test for unequal variances is done

Output:

Test result P: value = 0.2026

The P Value is less than 0.05, thus rejecting Ho. There is a significant difference between the unemployment rates in NC and TX.

Using the T test, there is a significant difference between the unemployment rate in NC and TX. That is, the unemployment rate in NC and TX is not the same.

The appropriate test for the given hypothesis to be tested is the t-test for independent samples

The assumptions and violations are provided in the explanation part.

Explanation:

The data is collected on the unemployment rates (UR) of the two states for the year 2019.

We are to compare between the mean unemployment rates of the two states.

The hypotheses formulated:

H₀: The Unemployment Rate in NC and TX is the same.

H₁: The Unemployment Rate in NC and TX is not the same.

Mathematically,

H₀:_NC= _TX

H₁: _{NC TX}

_NC= The UR of NC

_TX= The UR of TX

For the given hypotheses, we are to compare the presence of any statistically significant difference in the UR of TX and NC and thus, we need to conduct a test for finding the difference between the two groups.

The data collected for TX and NC can be compared using the mean UR for 2019 for TX and NC and check rather or not they are significantly different.

The data samples were collected independently from the two states for each month of 2019 and thus we try to find whether the difference between UR of TX and NC are statistically significant.

Thus, a t-test can be appropriate for the given problem and the appropriate test is the two sample T-test based on independent samples.

The assumptions when a T-test is conducted for independent samples :

• The data collected must be independent in nature.

Here, the data collected on UR for each month in 2019 for TX and NC are independent of each other.

• The data collected for a particular group must be a random sample of the population
• The data must be normally distributed
• The two groups for which the data is collected have equal variances

Violation of Assumptions:

• If the groups are not independent in nature, the appropriate test would be the paired sample T-test.

As from the data provided above, the observations are collected from different states, namely TX and NC, this problem would not arise.

• If the observations are not normally distributed, it is not appropriate to conduct any t- test paired or independent. The reason that the given test cannot be conducted if the sampleshave been collected from a normally distributed population is a very crucial assumption and if it is violated, conducting a t-test will give inappropriate results.

There are other Non-Parametric(NP) methods of testing to be considered to test the following hypotheses.

• The samples obtained may not have equal variances.

If the variances of the two groups are equal to be checked through the F test, we conduct the t-test for independent samples with unequal variances.

Conclusion: