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At 5% significance level, conclude before and after plan is different

The following table gives the blood pressures (in mm Hg) of seven adults before and after the completion of a special dietary plan.
Before
210
180
195
220
231
199
224
After
193
186
186
223
220
183
233
At the 5% significance level, can you conclude that the blood pressures before and after the completion of the dietary plan is different?

*** You will reply to 2 classmates’ threads. At least 1 paragraph in length. They must be on the

*** 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.

discussion

Statistics Assignment Help hi, i need help with my discussion and replies from my classmates.
Discussion: What techniques are used to solve decision-making problems under uncertainty? Which technique results in an optimistic decision? Which technique results in a pessimistic decision? Reply #1: What techniques are used to solve decision-making problems under uncertainty?
Minimax regret
Equally likely
Criterion of realism
Maximin (pessimistic)
Maximax (optimistic)
Which technique results in an optimistic decision?
Maximax criterion which finds other options that maximize the maximum payoff.
Which technique results in a pessimistic decision?
Maximin criterion which finds other options that maximize the minimum payoff. Reply #2: What techniques are used to solve decision-making problems under uncertainty?
Maximax (Optimistic)
Minimax Regret
Criterion of Realism ( Hurwicz)
Maximin (Pessimistic)
Equally likely (Laplace)
Which technique results in an optimistic decision?
It locates the maximum payoff for each alternative and selects the alternative with the maximum number.
Which technique results in a pessimistic decision?
The Maximin Technique results in a pessimistic decision by identifying all minimum payoffs for each alternative under each state of nature and selecting the alternative with the minimum possible payoff. It was also stated that, the “Do Nothing” alternative was identified to have the most minimum payoff.

Download the Competency 3 Reflection Data Set. The data set is information about the tax assessment value assigned to

Download the Competency 3 Reflection Data Set. The data set is information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database:

Floor Area: square feet of floor space
Offices: number of offices in the building
Entrances: number of customer entrances
Age: age of the building (years)
Assessed Value: tax assessment value (thousands of dollars)


As you work through the following exercises, note your answers to the given questions so you can easily summarize them in your reflection.



Use the data set to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics.



1. Construct a scatter plot in Excel with Floor Area as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and R2 in your graph.

Do you observe a linear relationship between the 2 variables?
2. Use Excels Analysis ToolPak to conduct a regression analysis of Floor Area and Assessment Value.

Is Floor Area a significant predictor of Assessment Value?
3. Construct a scatter plot in Excel with Age as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and R2 in your graph.

Do you observe a linear relationship between the 2 variables?
4. Use Excels Analysis ToolPak to conduct a regression analysis of Age and Assessment Value.

Is Age a significant predictor of Assessment Value?


Construct a multiple regression model.

Use Excels Analysis ToolPak to conduct a regression analysis with Assessment Value as the dependent variable and Floor Area, Offices, Entrances, and Age as independent variables.
What is the overall fit R2? What is the adjusted R2?
Which predictors are considered significant if we work with ?=0.05? Which predictors can be eliminated?
What is the final model if we only use Floor Area and Offices as predictors?
Suppose our final model is: Assessed Value = 115.9 0.26 x Floor Area 78.34 x Offices.
What would be the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago?
Is this assessed value consistent with what appears in the database?
**%$**?tual assignment **

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