## MODULE 1 DISCUSSION – Descriptive Statistics

MODULE 1 DISCUSSION – Descriiptive Statistics

In many realms of statistics, data are presented in many shapes and forms. One of the ways to make sense of data is through the use of descriiptive and inferential statistics. Discuss in detail these two aspects of data analysis using citations and references to validate your argument.

USE THIS VIDEO IF NEEDED
https://youtu.be/VHYOuWu9jQI

https://statistics.laerd.com/statistical-guides/descriiptive-inferential-statistics.php

## Program Analysis

Identify different programs at your school or place of work that would benefit greatly from including data analysis for overall decision-making processes.

STUDENT DISCIPLINE IS THE AREAD THAT I WOULD LIKE TO ANALYZE DATA. PLEASE USE THE Analyzing student-level disciplinary data: A guide for districts TO HELP ANSWER THE PROMPT BELOW.

In a two-page paper, outline steps to begin the process of problem identification, data collection, data analysis, data interpretation, and data presentation for one of the programs you identified.

## Week 5-(Statistics) response to Jeff Brown and Andrew Rowe

Please respond to these 2 answers in 2 separate paragraphs with a minimum of 175 words each paragraph.

Jeff Brown’s response, I’ve had to use hypothetical testing in my professional life when examining productivity. My null testing was whether or not restroom breaks were affecting the productivity. Which in turn you would assume the restroom breaks would immediately take up time where an assembly is not being produced. Of course throughout the testing I take plenty of notes to track the productivity and to ensure my hypothesis is still on track. My results concluded that restroom breaks did not affect productivity as much as I thought which made my research null since I thought originally that as much as some went I believed it affected their numbers. Most of it may contribute to regular fatigue and repudiation. These two factors slow down the workers and affected their numbers by twenty percent. These numbers were astounding to me as I originally thought that it was the restroom breaks. I have to admit I was not sure what it was called until this class I just was collecting data and comparing to a hypothesis I had in my teams productivity.

Andrew Rowe’s response, A hypothesis is a claim about a specific part of a population. When you are looking at aspects of a population and have an idea of what makes certain parts of it unique from the rest of the population, you test the hypothesis to see if it is true. There are many times that you would use hypothesis testing. I just moved into a new home on Friday, and the cost of my homeowners insurance rose quite significantly. I don’t know too much about the insurance industry, but I would venture to guess that they are always using this method and taking the results from different sub populations that they insure to determine costs. A one-tailed test is simply testing a specific variable to see if there is a significant difference in one direction. On the other hand, a two tailed-test tests variables to see if there is a significant difference in either direction.

At work, I make the schedule for a group of 48 people. In the hospital setting, it is hard to predict the need for staff as the number of patients in the hospital varies from time to time. Typically in the fall/winter time, it is busier in a children’s hospital as the kids in the community go back to school and expose each other to a slew of viruses. During the summer months, we are always well staffed and able to safely care for all of the patients requiring my group’s services. By October and all the way through April, we are chronically short staffed due to an increase in patients. A few years ago we tested the need for for staff in May-September vs October-April. We did this so that we could take the results to administration and make a case for spending extra capital to bring in travelers during the “surge” to help us out. We are now at the point that we have funds for travelers built into our annual budget for the “surge”.

Here is the original question. (You don’t need to answer, this is just to give you context)

## 501 1-1 Responses

*** You will reply to 2 classmates’ threads. At least 1 paragraph in length. They must be on the same page, but LABELED WHO’s is WHOSE. The first paragraph should be labeled (Jonida) and the other one should be labeled (Valeska LaPlanche) ****** When responding to your classmates, provide additional ideas and assistance for their proposed social science research questions. Make comparisons between your question and study plan to theirs, explaining the similarities and differences.

Valeska LaPlanche

Hi everyone! My name is Valeska LaPlanche and I am pursuing my master’s in Psychology at SNHU. I received a dual B.S. in Childhood Education and Life Sciences from Russell Sage College in May 2020. I decided to enroll at SNHU because it gives me the freedom that I need as a single foster mom and full-time Behavioral Intervention Specialist. Currently, I work at a non-profit supporting adults with intellectual and developmental disabilities and I love my job!
A. My social science research question is, “How do mental health concerns affect those living with intellectual disabilities?”

B. The population for my specific question is: individuals with dual diagnoses (i.e., intellectual disabilities and mental health concerns). I decided that I wanted to look at this population because through my work I have seen a distinct difference between how people with and without intellectual disabilities are treated during mental health crises. In much of my work, the individuals that I support do not receive the proper mental health care because their crisis is often chalked up to their disability and referred to as “behavioral.”

C. When looking into this question, I would use a stratified sampling. This sampling method is typically utilized when looking into non-overlapping subgroups that represent the entire population. I think this sampling method would be most appropriate, as the population I am looking at has many variations in intellectual ability and specific mental health concerns.

D. This study would be observational, as I would survey those participating without attempting to impact them. This would include observing what treatment options are open to those within the study in relation to mental health concerns.

Jonida
Hello everyone, my name is Jonida and this is my first class towards my master’s degree in Data Analytics.
How is social media effecting teen depression?
My population of interest will be all teenagers in US that suffer from depression.
I will be using cluster sampling. First, I will divide the teenagers into groups or clusters and then I will select some of the groups that I have created. Then, I will obtain the sample by choosing all the teenagers within each of the selected groups.
I will be using observation study. I will be observing how social media is affecting them. Is it making their depression better or worse? Do they turn to social media because they feel depressed, or they get depressed the more time they spend on social media?

MONTANA FULLER Is Below

Social science research question: “Does eating too much with less exercise cause obesity?”
My name is Tony Fuller, my major is Psychology. I’m currently working on my 3rd master’s degree from Southern New Hampshire University. My 1st master’s is in Criminology, my 2nd is in Sports Management that I received from SNHU also.
The rationale behind understanding the relationship between obesity, food and, exercise is that obesity is a major health issue among African American women in the United States. Generally, obesity prevalence in the United States exceeds 30% among African Americans (blacks) (Mehari et al., 2015). Specific samples show that obesity affects the rural population at 40%, for instance, African Americans living in Alabama at 42%, and Mississippi at 43% (Sterling et al., 2017). Therefore, it is vital to understand the aspects leading to such high trends among blacks compared to other populations, thus finding an ideal prevention technique. The objective of understanding obesity as a social problem helps eliminate health issues including heart diseases (cardiovascular diseases), respiratory diseases, and psychological issues (body shaming) that affect the general way of life of African American women.

The population under study is the African American women living in the rural South thus aiming to prevent body shaming and raise awareness of body image perception, thus promoting social health behaviors. Apart from the health challenges associated with obesity, women face psychological problems due to body shaming (Johnson et al., 2017). The study will understand the eating habits, ratios, and patterns for the African American women in rural South as they are the most affected population; hence through such results, one can understand their body mass index (BMI) and ways to lead a healthy socially active life.

Simple random sampling will identify the study population (African American Women) in the study area (Rural South). Simple random sampling entails identifying the population, then each individual is given a number as identity, and then a probability of selection for the study done (Health Knowledge, 2020). For instance, with a study of 500 selected individuals, a group of three or two digits is used to select the study population randomly. However, it is vital to note that only the qualified people are selected from the population through employing though elimination criteria including age, race, occupation, and other aspects that may affect the study results. The simple random sampling method allows the reduction of errors through reduced selection biases. Another reason for using the simple sampling method is that it is suitable for data analysis inferential statistics. Further, there is no room for biases while selecting the population to inform the study as numbers replace participants’ names, thus eliminating identity during the selection process. Therefore, the method is ideal and simple for studying the relationship between eating habits and obesity among African American women in the rural South. However, selecting individuals with similar required study characteristics from a large sample; thus, much information about the study is identified before engaging the population.

The research will use experimental study type (study and experiment groups) by providing dietary types to the study population within a specific period (3 months) while registering their body weight. Further, the experiment will include exercise inclusion as the population will register frequencies of taking exercises. The result of the study groups and experiment groups is compared to understand the effects of dietary types and exercises on obesity. The experiment will cover three months to find better answers and register better results. However, while experimenting, the study population will be advised, directed, and their lifestyle monitored to ensure they are on provided diet exercises. An analysis of the experiment group will lead to a comparison to the study group, and differences in study results will answer the study questions (Organization for Autism Research, 2020). However, variables such as stress caused by low-income, general poverty, and other social problems are identified to eliminate errors.