Category: Statistics

Instructions Lab 1
This Lab 1 consists of 15 multiple-choice questions that will ask you to apply practices covered by the assigned lab activities. To be successful with Lab 1, it’s important to thoroughly read and work through assigned activities for Lab 1. It will also be beneficial to review the lab session recording

The files you need to complete the assignment are attached below. It requires you to use measurement and statistical packages (e.g., SPSS, GENOVA, and/or calculator) to complete the exam. 

1. The term statistics elicits a wide range of responses among anyone who hears it, many of which are either wrong or partially correct.
Taking into consideration your previous experience along with this week’s readings and videos, how has your perception of statistics changed?
Using either your current role or a previous organizational role, describe an issue from your experience that may have resulted from misunderstanding or misusing descriptive statistics.
2
Complete Exercises 6, 7, and 8, on page 115 of Green and Salkind (2017).
In a separate Word document, develop an APA formatted deliverable that presents the results of Michelle’s research question.
Homework responses should include information regarding:Any survey item(s) that had responses recoded
Mean Attitudinal scores for Republican and Democrat respondents
APA formatted boxplot that represents Total Attitudinal scores by political affiliation
Turn in your SPSS output file as a separate PDF document.
There is a 200 word limit with a 50-word buffer for this assignment. Submissions that surpass the limit and buffer will be subject to a two-point (8%) penalty.

https://www.statcrunch.com/app/index.html?dataid=4375823# – website for Freshman
_15
Background
Many college students are familiar with the term “Freshman 15” which is referring to the average 15-pound (6.8 Kg) weight gain that students my incur during their first year in college.  The reasons students may gain weight will vary.  Certainly, a change in eating habits, lack of exercise, long hours of studying and being sedentary, stress and anxiety are just a few examples of what can cause weight gain.  For this activity, you will use a dataset to evaluate before and after weights for both males and females by conducting summary statistics, graphing your data, and drawing some overall conclusions based on your analysis.   
Instructions
Part I:
Conduct this activity in MyLab by Pearson
Summary Statistics: 
Select “Content” from the Brightspace Navigation toolbar.  
Select “MyLab Statistics” from the “Content” menu.
Click on the “MTH 210 StatCrunch” tab
Click on “Open Link”
Select the “StatCrunch Website”
Under the Data Column > select “Data Sets”
Search for the data set “Freshman_15” and select the data 
Analyze your data using the Stat pull-down menu:
Stat> Summary Stats> Columns
Click “WT SEPT” to move to the right panel
In “Group by”, select “Sex” from drop down menu
Select “Compute!” At the bottom right.
Copy and paste your results into a word document
Repeat the steps above just selecting for b. “WT APRIL” and copy and paste your results into the same word document. 
Graphs:  
You may choose histograms (1) or boxplots (2) to represent your data.  If you choose histograms, you will create 4 graphs: WT SEPT Female, WT SEPT Male, WT APRIL Female and WT APRIL Male. 
If you choose boxplots, both genders can be represented in the same display for a total of 2 graphs for both months. 
Histograms (4 graphs total)
Graph > Histogram
Click “WT SEPT” to move to the right panel (repeat all steps again for “WT APRIL”)
In “Group by”, select “Sex” from drop down menu 
Select markers (mean and median)
Select “Compute” At the bottom right.
Copy and paste your graphs into a word document (there will be one for F and one for M as you arrow over in your results)
Boxplots (2 graphs total)
Graph>Boxplots
Click “WT SEPT” to move to the right panel (repeat all steps again for “WT APRIL”)
In “Group by”, select “Sex” from drop down menu
Select markers (mean and median)
Hit Compute! At the bottom right. 
Part II: Interpretation and Conclusions
Answer the following questions in the submission box below:
Use your knowledge from Module 1 to discuss the following: 
How did the average weights change from September to April for males and for females?
Look at the median.  Was there a significant shift between the months for males and females?
Describe the shape of the distributions of the graphs for both genders.  Were there any potential outliers causing skewness in the data for either month?
Give your overall conclusions based on your analytical results.  In this dataset, does it appear that gaining 15 lbs (6.8 Kg) on average is accurate over this time frame (a statistically significant change)? Explain. 
Additional Resources
MyMathLab: Video & Resource Library > StatCrunch Tutorial Videos (Computing summary statistics, Creating histograms and Creating boxplots) 

Take a screenshot of the solution to each question and upload the PDF file of all the merged screenshots.

The subject is actually economitrics, so you should combine statistics things and economic things.
This project is a critique of this semester’s paper. The critique will be based on one main point. It means that, although you may know several things that are wrong with the paper, your project will discuss only one. Of course, choose the best one you can. You introduce the point which will be the basis of your critique. You have to explain what your point is, then you have to provide evidence for this point, and finally you have to describe the consequences for the results of overlooking your critique point. For example, if you are defending that there is an omitted variable, you must explain what is the consequence of this omission: is the bias positive or negative? What is the consequence of this for society? Finally, you must have a conclusion. Don’t forget the bibliography, if applicable. It must follow a standard academic style. Any style is fine, as long as it is the same for all entries. Turabian (also known as Chicago style) is a good choice, very well accepted in Social Sciences.
The critique point must be specific. Is it omitted variable bias? Then you must defend that 1 specific variable was omitted. Which is it? Is it measurement error? Then which variable has measurement error? Is it sample selection? Then are you concerned with selection in which specific way? You must provide evidence, and you can go as far as you want there. You can use pure logic, you can use newspaper sources. However, the best evidence comes from actual research papers. If you want to really impress, you can bring outside datasets. There is no limit to the creativity you can put into the evidence for your point. Moreover, if you can solve the problem, then you should. It is not necessary to do this, but it certainly increases the level of impressiveness of your project to a whole new level.
The project has strict formatting rules. The paper cannot have more than 8 pages counting everything (except the cover page). It must be written in single-space, Times New Roman font size 12. The document must leave 1 inch of space in all margins, no more, no less. Pages must be numbered. Include a cover page with your name, student ID, and class time. Here are some guidelines (not obligatory) to help you write the paper: a typical critique has a 2 page long introduction, then the critique itself is introduced briefly in about half a page. The body of the critique is very free, and the conclusion is usually at most one page long.
The project is graded based on many things. First, the introduction where you summarize the paper. There we are looking for an excellent understanding of what truly matters in this paper. The words about which you should think are conciseness, precision, and readability.
The body of the paper is, of course, the most important part. We are looking for a good critique point, which is defended using excellent evidence. The critique must clearly delineate what are the consequences of the problem you are raising. We reward creativity very highly. You can defend the same critique point as many of your colleagues, but then you are in direct comparison with them. If you choose an unexplored critique point, you will be evaluated on your own, which is a good thing. Moreover, when we see a novel critique point, we imagine that you thought about, but rejected, several more common ideas. Hence, we will reward you directly. We also reward the quality of the evidence. Not all evidence has the same strength and reliability. It goes like this: straight from data¿¿research papers¿¿online verifiable journalistic sources¿¿logical argument. This is not written in stone, but it’s a decent guideline. We reward effort and creativity involved in choosing, searching, and using the evidence. We also reward the strength of your whole argument. Is it easy to understand? Are you convincing?
You can make up for things. For example, you may not be defending the most creative critique point, but you can make up for it with a brilliant evidence source, or even (wow!) a direct solution. Additionally, this is an essay, so your language counts a lot. We establish just a few points for style and grammar, but don’t underestimate the power of a well written piece. An argument that develops fluidly, a paper that is not boring, a paragraph that is so well structured that the mind just cruises through it, all of those end up reflecting in your final grade. We punish pretty severely when your arguments are not clear, when we have to re-read things many times to get the point. I do not need an introduction paragraph, so please go directly to the critique part.

I have uploaded the Rubric/Guidelines, Module Overview, Reading and resources, and chapters from the textbook.

Instructions
A new
migraine medication is in development, and the developers are curious to see
the impact it has on Men v Women. The medication was given to 13 Men and 13
Women, and the participants were asked to identify how long it took for them
(in minutes) to feel initial relief from their migraine. The results are
provided below:  
Men –
3,8,15,32,21,45,78,73,72,85,23,35,45 
Women
– 3,9,2,15,27,32,35,54,45,37,24,27,31 
For
each group individually, find the five number summary, as well as the mean and
sample standard deviation. Using the boxplot calculator (link below), produce
side-by-side boxplots of Men v Women.
Use the following calculator to
produce side-by-side boxplots: https://goodcalculators.com/box-plot-maker/Links to an external site. You can copy/paste
the values above into the correct cells in the calculator. Do not add any
spaces. 
Discussion
Prompts
Answer the following questions in your initial post: 
1.       
Report
your five-number summary, mean, and sample standard deviation. Do not forget,
we are looking at a sample set here, so we need to use the sample standard
deviation. 
2.       
Describe
how the summary statistics for the group of Men compare to the summary
statistics for the group of Women
3.       
Post
your created side-by-side boxplots. From the visual, what can we say on an
objective level about the two groups? 
Supporting Resources: https://www.youtube.com/watch?v=QoQbR4lVLrsLinks to an external site. 
If possible, respond to posts that have not yet
received responses from classmates. 

This has to be done using excel and you have to make sure you use the right functions and that you know hoe to use excel 

Sustainable communities are the product of
strategic decisions, actions and investments guided by an underlying theory that
can be tested through empirical evidence and adjusted (Bridge between Theory
and Practice) to more accurately reflect reality.  Models are often contextual in nature and
must either, be modified for each context or model builders must strive for
generalizability.  For the third paper, you
are part of a policy team that advises key community leaders and public
officials of the Wichita-Sedgwick County region on the Preliminary Model for Building Community Capacity in
preparation for the Perfect Storm. The intent of the policy team is
to test the proposed model and to provide insight about possible actions and
Calculation Section 
·     
Provides calculations
·     
Provides a conceptual description of the logic
behind the statistic using the example
Provides calculation provided in the codebook and 
A
Pearson’s Correlation Coefficient (PCC) is a statistical quantitative measure
that determines the range and direction of the linear relationship between two
variables (Statistics How To, 2020). The Different Factors the Public Interest
Index (PIIDX) scores and the Trust Index (TRUSTIDX) scores can be applied to
obtain Pearson’s Correlation Coefficient.
The
formula for Pearson’s Correlation Coefficient is:
r
= Σ[(x – x̄)(y – ȳ)] / √[Σ(x – x̄)² Σ(y – ȳ)²]
Where:
r = Pearson’s Correlation Coefficient x = PIIDX score y = TRUSTIDX score x̄ =
Mean of PIIDX scores ȳ = Mean of TRUSTIDX scores
For
computing the correlation, it is essential to first obtain the respondent
scores on the PIIDX and TRUSTIDX items from the survey data. Secondly, the mean
score for both the PIIDX and TRUSTIDX can be computed. These values can be
inputted into the formula to determine Pearson’s r value for each respondent.