A chair with a mass of 20.0 kg is attached to one end of a frictionless pulley system via a
a strong massless rope. The other end of the rope is attached to a steel water tank sitting on a flat horizontal concrete surface (see the image to the right). The coefficient of static friction between steel and concrete is 0.45 and the coefficient of kinetic friction between the surfaces is 0.30. The water tank, which is full of water, has sprung a leak. The combined mass of the water and the tank is 500 kg. This mass slowly decreases as the water leaks from the hole. You (i.e. your entire mass) are sitting at rest in the seat. You and the seat will remain at rest as long as the force of static friction is strong enough to hold you.
LET [DOWN] and [RIGHT] be positive. Using your knowledge of physics, determine the following:
Draw the FBD of the system of you and the chair while at rest. Using the LET statement above, write out the net force equation. 
Draw the FBD of the system of the water tank at rest on the flat horizontal surface. Using the LET statement above, write out the net force equations for both the vertical and horizontal planes. 
Using the net force equations, determine the minimum mass of water that must be lost (i.e. leaked out) from the water tank in order for you and the seat to begin falling? 
As soon as the chair begins to move, static friction between the steel tank and concrete surface becomes kinetic friction. Determine the magnitude of the kinetic friction. 
Using Newton’s 2nd law, determine the acceleration of the system at the instant that the static friction becomes kinetic friction. 
2.1) (Ch. 7) Explain what a residual is (also known as residual of prediction).
e idea of “least squares” in regression (you need to fully read pp. 200-208 to understand).
3) What does it mean if b = 0?
4) What does it mean when r-squared is 0? What does it mean when r-squared is 1?
5) What is the difference in an unstandardized regression coefficient and the standardized regression coefficient?
6) If a report says test performance was predicted by number of cups of coffee (b = .94), what does the .94 mean? Interpret this. (For every one unit increase in ___,There is an increase in ___ )
7) If F (2,344) = 340.2, p < .001, then what is this saying in general about the regression model? (see p. 217)
8) Why should you be cautious in using unstandardized beta? (p. 218)
9) (Ch. 8) Explain partial correlation in your own words. In your explanation, explain how it is different from zero-order correlation (aka Pearson r).
10) (Ch. 9) What is the F statistic used to determine in multiple regression?
11) What is F when the null hypothesis is true?
12) In Table 9.4, which variable(s) are statistically significant predictors?
13) In Table 9.4, explain what it means if health motivation has b = .36 in terms of predicting number of exercise sessions per week.
14) What is the benefit of interpreting standardized beta weights? (see p. 264).
15) What happens if your predictor variables are too closely correlated?
16) Reflect on your learning. What has been the most difficult? How did you get through it? What concepts are still fuzzy to you? Is there anything you could share with me that would help me address how you learn best?
You are asked to carry out a study on behalf of a business analytics specialised consultancy on a subsample
on a subsample of weekly data from Randall’s Supermarket, one of the biggest in the UK. Randall’s marketing management team wishes to identify trends and patterns in a sample of weekly data collected for a number of their loyalty cardholders during a 26-week period. The data includes information on the customers’ gender, age, shopping frequency per week and shopping basket price. Randall’s operates two different types of stores (convenient stores and superstores) but they also sell to customers via an online shopping platform. The collected data are from all three different types of stores. Finally, the data provides information on the consistency of the customer’s shopping basket regarding the type of products purchased. These can vary from value products, to brand as well as the supermarket’s own high-quality product series Randall’s Top. As a business analyst you are required to analyse those data, make any necessary modifications in order to determine whether for any single customer it is possible to predict the value of their shopping basket.
Randall’s marketing management team is only interested in identifying whether the spending of the potential customer will fall in one of three possible groups including:
• Low spender (shopping basket value of £25 or less)
• Medium Spender (shopping basket value between £25.01 and £70) and
• High spenders (shopping basket greater than £70)
For the purpose of your analysis you are provided with the data set Randall’s.xls. You have to decide, which method is appropriate to apply for the problem under consideration and undertake the necessary analysis. Once you have completed this analysis, write a report for the Randall’s marketing management team summarising your findings but also describing all necessary steps undertaken in the analysis. The manager is a competent business analyst himself/herself so the report can include technical terms, although you should not exceed five pages. Screenshots and supporting materials can be included in the appendix.
After completing your analysis, you should submit a report that consists of two parts. Part A being a non-technical summary of your findings and Part B a detailed report of the analysis undertaken with more details.
Part A: A short report for the Head of Randall’s Marketing Management (20 per cent). This should briefly explain the aim of the project, a clear summary and justification of the methods considered as well as an overview of the results.
Although, the Head of Randall’s Marketing Management team who will receive this summary is a competent business analytics practitioner, the majority of the other team members have little knowledge of statistical modelling and want to know nothing about the technical and statistical underpinning of the techniques used in this analysis. This report should be no more than two sides of A4 including graphs, tables, etc. In this report you should include all the objectives of this analysis, summary of data and results as well as your recommendations (if any).
Part B: A technical report on the various stages of the analysis (80 per cent).
The analysis should be carried out using the range of analytics tools discussed:
• SPSS Statistics
Ensure that the exercise references:
• Binary and multinomial logistic regression
• Linear vs Logistic regression
• Logit Model with odds Ratio
• Co-efficients and Chi Squared
• MLR co-efficients
• Assessing usefulness of MLR model
• Interpreting a model
• Assessing over-all model fit with Psuedo R-Squared measures
• Classification accuracy (Hit Ratio)
• Wald Statistic
• Odd ratio exp(B)
• Ratio of the probability of an event happening vs not happening
• Ratio of the odds after a unit change in the predictor to the original odds
• Residuals analysis
• Cook’s distance
• Adequacy (with variance inflation factor VIF and tolerance statistic)
• Outliers and influential points cannot just be removed. We need to check them (typo? – unusual data?)
• Check for multicollinearity
Write a short and concise report to explain the technical detail of what you have done for each step of the analysis.
The report should also cover the following information:
• Any type of analysis that might be useful and check whether the main assumptions behind the analyses do not hold or cannot be
• Give evidence of the understanding of the statistical tools that you are using. For example, comment on the model selection procedure and the coefficient interpretation, e.g. comment on the interpretation of the logistic regression coefficients if such a method is used and provide an example of
• Conclusions and explanation, in non-technical terms, of the main points
4.. A uniform cylinder of mass M and radius R is initially at rest on a rough horizontal surface. A
ght string is wrapped around the cylinder and is pulled straight up with a force T whose magnitude is 0.8 Mg. As a result, the cylinder slips and accelerates horizontally. The moment of
inertia of the cylinder is I = 12 MR2 and the coefficient of kinetic friction is 0.4.
a. On the diagram above show all the forces applied on the cylinder. b. Determine the linear acceleration a of the center of the cylinder. c. Determine the angular acceleration α of the cylinder.
d. Explain the difference in results of linear acceleration a and αR.