DATA Analysis

SECTION 1

  1. The following table shows the demand and supply for a popular pair of shoes sold by Akron Enterprise Limited (AEL).
    TABLE 1
    Price per pair $ Quantity Demanded Quantity supplied Market Condition Pressure on price
    105 25000 75000 Surplus
    90 30000 70000
    75 40000 60000 Downward
    60 50000 50000
    45 60000 35000
    30 80000 20000 Shortage
    15 100000 5000 Upward
    Other information regarding AEL are as follows:
    Fixed Cost = $2000 Variable Cost = 20Q
    Answer all the following questions:
    a. Complete the table above: [10 marks]
    b. Graphically illustrate market equilibrium using the information in the above table. [4 marks]
    c. Calculate and interpret the price elasticity of demand using the midpoint formula as the price of a pair of shoe rises from $60 to $75. [8 marks]
    d. Explain and graphically illustrate a price floor implemented by the government using an appropriate price in the table above. [4 marks]
    e. If Akron Enterprise Limited sells its product at the equilibrium price, calculate total revenue and total profit. [6 marks]
    f. At what level of price(s) identify above is a shut-down price for Akron Enterprise Limited. [4 marks]
    g. Graphically illustrate the shutdown position for a typical firm. [4 marks]

Sample Solution

Data Analysis

Interpret the results from the analyses you have performed thus far. Some of this may involve some repetition from your earlier submission of your preliminary analysis. The purpose of this submission is to demonstrate that you have moved further along in your analysis and are ready to provide an interpretation of results that are useful for your original questions in your proposal. In your previous submission, you may have encountered issues in your analysis that have hopefully by now been resolved. The paper should look pretty close to the completed paper.

This submission should include:

A brief summary of the problem you are addressing
A complete discussion of all analyses you have conducted thus far. Much of this can be taken from your earlier submission on your preliminary analysis, along with any changes you have made to your earlier analyses and any additional analyses you have conducted.
An interpretation of the results of your analyses, including:
Interpretation of any statistical results (e.g. coefficients from regression, odds rations, ANOVA tables, etc.)
Interpretation of fit statistics of the results (p-values, R-squared values, AUC, etc.)
Visualizations to help clarify the output of your analyses. These could include (but are not limited to):
Plots of dependent versus independent variables
Average values of target variables for different categories of independent variables
Heat maps
Discussion of the implications of these results.
How are they valuable in answering your original questions?
Do the results provide answers to the questions you originally asked?

Comments from Customer
This is the requirement for preliminary analyses:
Briefly discuss the problem you are addressing and the questions you are trying to answer. Much of this can be carried over from your proposal with some modification.
Discuss the data that you are using
Where did you get it?
What fields does it contain?
What does each row in the data contain
What did you have to do to get the data into a format that is ready for analysis
Discuss the types of analysis that you have run to attempt to answer your questions.
Provide some output of each analysis. This could include:
Statistical output, if a statistical output is conducted
Aggregate tables
Charts
A brief discussion of the preliminary findings
Are the analyses you have run helpful in answering your question?
Has your preliminary analysis made you re-think any of your original assumptions or the questions you are trying to answer
What is your next step? What additional analyses will you run?

Sample Solution

Data Analysis

Analyze the data using SPSS, ANCOVA, Pearson Correlation, Chi-square analysis and develop graphs as well table(example: characteristics of participants and others as stated in chapter 4).

Explain the results of the analysis

Sample Solution

Data Analysis

student
Run cluster Analysis (in Stata or R) for Segmentation on the PDA 2001 data to try to identify the number of distinct segments present in this market. (2 pts)

2.Identify and profile (name) the clusters that you select. Given the attributes of ConneCtor, which clusters would you target for your marketing campaign? (2 pts)

3.How has this analysis helped you to segment the market for ConneCtor? (0.5 pt)

4.What concerns do you have with the approach (data collection, analysis, etc.) so far?

Sample Solution

Data Analysis

Steps for data analysis:

  1. Rename my variables into something that is easily recognizable.
  2. Use the frequencies command on my categorical variables to get an idea of how my data set looks – this will be important for methods section to write about stuff such as how many men vs women you sampled.
  3. Use the compute command to create a Mean or a Sum score for participants’ ratings of YouTube, using only those who responded to every question on my survey.
  4. Next you need to filter out people who didn’t meet the criteria for my analysis, such as those who didn’t attend the University of Hail.
  5. If you run the descriptives command for my rating variable, you should have an N (sample size) of 742. This is also where you’ll find the mean/standard deviation.
  6. Next you need to run the following analysis: a Factorial ANOVA.
  7. Now, run the same analysis, but remove any nonsignificant interaction terms. Make sure to include post-hoc tests for predictors with more than two levels that are significant. You need also use the plot function to graph anything you feel you need to. Also you have to talk about specific means (such as men vs women), report estimated marginal means. You also want to include measures of effect size. You would also run homogeneity tests to see if my data fits the assumptions of the test.
  8. If you ran the first analysis according to these steps, you should have 742 under the “df” column in the “total” row of the between-subjects table. For the second analysis, this should be 804. These are degrees of freedom, and they correspond to my sample size.
    you should end up with 742 sample sizes and if you did get there then you did what I did exactly and you’re on the right track and good to go.

Steps for writing results:

  1. You essentially you need to start by specifying exactly what type of test you ran, such as: “A 2 x 2 x 4 mixed factorial analysis of variance was conducted.” This is determined by the number of levels your variables have, and whether they are within or between subjects.
  2. You then need to state what your outcome variable was, and what your independent variables were, along with the levels of those variables.
  3. Next, you should talk about significant interactions if they are there. If not, mention that there were no significant interactions and talk about main effects (report significant and nonsignificant effects). Here are examples of the format for how to report F statistics from previous work I have done:
    There was no main effect of biological sex, F(1,603)= .095,p>.05,η ̂^2= .002.
    There was also a main effect of perception source, with victims reporting greater relationship violence than perpetrators, as well as a main effect of relationship duration, F(1,603)=25.95,p< .001,η ̂^2= .04 and F(4,603)=7.64,p< .001,η ̂^2= .05, respectively.
  4. Here’s what the different pieces are/mean:
    F(1,603) – this is denoting that you ran an F test, with the degrees of freedom for the variable on the left, and the total degrees of freedom on the right
    = 25.95 – this is the value of the F test
    p < .001 – this is the significance of the F test. Generally you report one of the following numbers: > .05 if the result was nonsignificant, or < .05, < .01, < .001, whichever is closest to your result.
    η ̂^2= .05 – This is called “eta squared”, it is a measure of effect size. Basically, how much your variable influences the outcome.
  5. If you have a significant variable with more than two levels, you should talk about those differences using post-hoc tests of pairwise comparisons. Make sure to specify which post-hoc tests you ran and how you controlled for familywise Type I error (not all tests do this automatically). Here’s an example of how to write about these from previous work:
    Among perpetrators, males reported less average relationship violence than females, p < .001.
  6. For the violations of the test assumptions, consider mentioning them somewhere.
    Ibecause I want to know more about what these violations are/how to identify and remedy them, a search for “ANOVA test assumptions” should help.

Here’s an example of an APA format graph – you can modify the labels and font, etc, in SPSS:

Figure 1. Estimated mean ratings of perceived violence in relationships for victims by biological sex and perceived relationship duration (N =61

Sample Solution

Data Analysis

Choose the data from this website: https://github.com/rfordatascience/tidytuesday. And follow this website to see which code you may need to use: http://ritsokiguess.site/STAC32/notes.html. Last, please provide the word docs file at the end. Thank you so much.

Data Analysis

Math 565 Homework #5

  1. Averages. Here are three commonly used measures for the central tendency of a set of numerical data items:
    • Mean: Add the items and divide by the number of items.
    • Median: Arrange the items in numerical order and locate the item “in the middle” (or if there are two “middle” items, then take their average).
    • Mode: The item that occurs most often.

Suppose a student got these grades on different tests. (Each score is out of a maximum of 100 points.)
80, 90, 85, 90, 50, 78, 84

a. Find the value of each of the three measures of central tendency for this set of numbers.

b. Suppose you needed to assign a single number as a grade for this student. Discuss the strengths and weaknesses of each of the three measures of central tendency as a method of choosing this number. Also state what number you would actually choose. (You can choose one of the answers to part (a) or something different from any of them.) Justify your choice

  1. Bias. In everyday language, the word “bias” is often used to mean an unfair judgment, especially against a particular racial or ethnic group. In polling, it refers to
    a built-­‐‑in imbalance in the sampling process, which may occur without any malicious intent. Thus, a poll with a biased sample might not give correct information about the larger population, because it may slant the results in a certain direction, even if the pollster doesn’t have that intention. In this assignment, you will look at ways in which bias might enter into the polling process for a particular situation.
    Suppose a student government committee wants to know whether $45 per ticket is too much to charge for a homeless shelter benefit concert at college. The committee decides to poll some students and use the results to help them determine if that price is too high.

Explain what might be wrong with each of these following methods of choosing a sample. How might it bias the results? What incorrect impression might we get?
a. Picking every tenth student who drives into the parking garage.

b. Stopping several groups of students coming out of the student union together and asking everyone in each group.

c. Picking one mathematics class at random and polling all the students in that class.

  1. Representative Samples. When you want to test hypotheses about some population, we can’t usually test the entire population. You usually need to pick a sample that is likely to represent the population accurately. Consider each situation below and answer the questions.
    a. A music producer wants to find out what college students think about various types of popular music. The producer conducts a survey around the video games area of the student union. What is an example of a conclusion the producer might reach based on this survey that might not be true about college students in general?

b. An auto manufacturer wants to conduct on-the-street interviews to find out what adults in the United States think of the company’s latest TV advertising campaign. The interviewer decides to use the people standing at the bus stop near her home throughout the day as the sample population.
What is an example of an erroneous conclusion one might draw from this population?
What might be a more representative sample of the audience targeted by the advertisement?

  1. Your own survey. When we talk about a population in common English, it usually refers to human beings. In statistics, it can refer to any set of objects. For instance, we might wonder about a feature of shirts or plants.

We’ll use our own environment such as our classes, work or home to gather numerical information from objects (not necessarily people). This should result in twenty numbers, each the represents some feature of the data. For example, I could record the number of buttons on 20 shirts at my house as my data.

a. Decide what numerical data to collect, present the data you gathered, and describe your process for gathering it.

b. What are the mean, median, mode of your data? Do any of the averages express a “typical” element of your data? Explain why or why not.

c. To draw a conclusion from my data that is a statement about some population I have to be careful. If I collected the numbers of buttons on 20 shirts around my house, those numbers may not be typical of all shirts in the universe. First of all, Other countries might have shirts with different numbers of buttons. I might prefer one type of shirt or shirts for women (like me) might have a different number of buttons than shirts for men. So I can only draw a conclusion about a population for which my sample is likely to be representative.

State a conclusion you could make about your population based on the sample data you collected. For example, I might say, “Shirts for American women have a mean number of buttons equal to 6.5.” Explain why you think the sample is representative of your population.

  1. Representations of Data. Here is a list of midterm grades (out of 100) for a professor.

77, 96, 58, 100, 66, 76, 88, 73, 94, 75, 76, 84, 91, 74, 87, 92, 67

Here are a few different representations of the data along with the grades she assigned to
the midterms.

a. Explain how she decided which numerical score received which letter grade.

b. If another student were to receive an 81 on the midterm, what grade do you think she would receive and why?
c. Explain, so that a middle school student could understand, how to interpret each of the four representations and exactly how you would construct each of the charts from the data.

Note: To figure out the last one you need to know it is based on dividing the data into four groups with equal numbers of data points.
d. Explain one advantage each representation has over the other three.

Sample Solution

Data Analysis

Analyze the data using SPSS, ANCOVA, Pearson Correlation, Chi-square analysis and develop graphs as well table(example: characteristics of participants and others as stated in chapter 4).

Explain the results of the analysis

Sample Solution

Data Analysis

Submit a .html, produced in .Rmd,
The task essentially asks you to (1) source your own dataset, and then (2) invent some research questions and investigate the different variables. (3) Write a reproducible report using R Markdown. (4) Present a 5 minute summary of the data and your findings.

There are many excellent data depositories, for example see
http://data.gov.au/
http://bigdata-madesimple.com/70-websites-to-get-large-data-repositories-for-free/
https://www.springboard.com/blog/free-public-data-sets-data-science-project/

Sample Solution

Data Analysis

Analyze the data using SPSS, ANCOVA, Pearson Correlation, Chi-square analysis and develop graphs as well table(example: characteristics of participants and others as stated in chapter 4).

Explain the results of the analysis

Sample Solution