What issue or information set does this visualisation cover?
What specific problem or question is it / are you trying to resolve?
What specific investigational goals do you have?
What specific techniques are used to achieve those goals?
What motivates spectators to attend sporting events?
What public support exists for the inclusion of esports in the Olympic Games?
To what effect have students used online platforms to ensure a sense of community during lockdown?
Using the Module Three Assignment Template Word Document, specifically address the following:
Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
Determine r: Determine r and what it means. (What is the relationship between the variables?)
Determine the strength of the correlation (weak, moderate, or strong).
Discuss how you determine the direction of the association between the two variables.
Is there a positive or negative association?
What do you see as the direction of the correlation?
Examine the Slope and Intercepts: Examine the slope b1 and intercept b0
Draw conclusions from the slope and intercept in the context of this problem.
Does the intercept make sense based on your observation of the line of best fit?
Determine the value of the land only.
Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Does this value make sense in context?
Determine the R-squared Coefficient: Determine the R-squared value.
Discuss what R-squared means in the context of this analysis.
Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
Is the square footage for homes in your selected region different than for homes overall in the United States?
For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
DATA ANALYTICS
Big data orientated application techniques
– Generating / obtaining data (1000 rows min)
– Hypothesis Testing
– Analysis & Visualisation
– Data Governance
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Generating OR obtaining relevant data set from a website, e.g. a statstics one. (can get from: or other sources. carry out analysis on the data set, and discuss governance.
You can create the data if that will be easier, it can be all made up but something relating to technology company.
4 main tasks summed up in the brief. please only assign a UK writer and expert in data analytics.
Is Community-Based Provision of Sterile Injecting Equipment Effective in Reducing Hepatitis C Diagnoses among People who Inject Drugs?Discuss
Describe the source(s) of the data and how each variable is measured.
Discuss the estimation strategy you adopt, the potential econometric issues that may be relevant and how you plan to deal with them. Also discuss any estimator, tests and approaches you intend to apply to support your arguments in your analysis.
Properly present the econometric estimates and evaluate the model performance in terms of goodness of fit and diagnostic tests.
Interpret the estimated coefficients, and describe whether they correspond to your expectations in light of the literature/theories
Discuss the results of other specification tests, hypothesis tests, robustness analysis (if you have conducted any) and report your findings.
Does the estimated equation support the theory on which it is based or the rationale in your mind? What explains any discrepancy between theory and empirics?
How do the results compare with existing findings? What new insights your results have added?
Are education degree and political views related?
From the ANALYZE menu
Choose DESCRIPTIVES
Choose CROSSTABS
Click on STATISTICS button
You will see a Dialogue box
Click on the CHI-SQUARE box in the upper left corner, click “expected frequencies”
Click CONTINUE
We want to look at “DEGREE” (columns box) and “POLVIEWS” (row box)
Look to the “Pearson Chi-square” information in the first row.
Chi-square=___________________ with ________ degrees of freedom and a p-value of_____________________. We have/do not have evidence to reject the null hypothesis that these variables are independent.
It appears that… (describe the association seen here if there was one)________________________________________________________________________________________________________________________________________________________________________________.
2. For your Lab Submission:
Examine the relationship between respondent’s health (HEALTH) and social class (CLASS). Treat social class as the independent (column) variable and health as the dependent (row) variable. Interpret results by reporting similarly to the above example. Be sure to report your results of the Chi-square value, degrees of freedom, p-value, and then your decision to reject the Null Hypothesis or not. Describe these findings in your own words.
Add SEX as a control variable (Under LAYER box which is under the Row and Column boxes) and calculate. Is the relationship stronger for women or men? Why might this be?
Compare and contrast a between-groups design and a within-subjects design.
What information about variables, levels, and design should you keep in mind in order to choose an appropriate statistic?
Provide an example of a study, including the variables, level of measurement, and hypotheses, for which a researcher could appropriately choose two different statistics to examine the relations between the same variables. Explain your answer.
What statistic would you use if you wanted to see if there was a difference between three ethnic groups on math achievement? Why?
What statistic would you use if you had one independent variable, geographic location (North, South, East, West), and one dependent variable (satisfaction with living environment, Yes or No)?
What statistic would you use if you had three normally distributed (scale) independent variables (weight of participants, age of participants, and height of participants), plus one dichotomous independent variable (academic track) and one dependent variable (positive self-image), which is normally distributed?
Explain your answer.
QUANTITATIVE ANALYSIS: DESCRIPTIVE STATISTICS, ORDINAL SCALE AND DICHOTOMOUS VARIABLE ASSIGNMENT
SPSS Problems
Chapter 4
Using the CollegeStudentData.sav file (see Appendix A), do the following problems. Print your outputs and circle the key parts of the output that you discuss.
For the variables with five or more ordered levels, compute the skewness. Describe the results. Which variables in the dataset are approximately normally distributed/scale? Which ones are ordered but not normal?
Do a stem-and-leaf plot for the same-sex parent’s height split by sex at birth. Discuss the plots.
Which variables are nominal? Run Frequencies for the nominal variables and other variables with fewer than five levels. Comment on the results.
Do boxplots for student height and for hours of study. Compare the two plots. Make Sure
What is the mean visualization test score?
What is the skewness statistic for math achievement test?
What does this tell us? What is the minimum score for mosaic pattern test? How can that be?
Using Output 4.1b: (a) For which variables that we called scale, is the skewness statistic more than 1.00 or less than –1.00? (b) Why is the answer important? (c) Does this agree with the boxplot for Output 4.2? Explain.
Using Output 4.2b: (a) How many participants have missing data? (b) What percent of students have a valid (non-missing) motivation scale or competence scale score? (c) Can you tell from Outputs 4.1 and 4.2b how many are missing both motivation scale and competence scale scores? Explain.
Using Output 4.4: (a) Can you interpret the means? Explain. (b) How many participants are there altogether? (c) How many have complete data (nothing missing)? (d) What percent are in the fast track? (e) What percent took algebra 1 in h.s.?
Using Output 4.5: (a) 9.6% of what group are Asian-Americans? (b) What percent of students have visualization 2 scores of 6? (c) What percent had such scores of 6 or less?
