3.It has been argued that of the two types of authoritarianism, left-wing has more in common with totalitarianism. To begin
litarianism. To begin with, provide a full description of left-wing authoritarianism. Then identify two traits of totalitarian syndrome and explain why you believe they support the assertion that left-wing authoritarianism is more similar to totalitarianism.
There are different understandings as to the nature of representation in an indirect democracy. Name and describe each type. Finally, explain which of these you could expect to find in the parliamentary system and why.
What, in the parliamentary context, is confidence? Why is it important, how might it be lost, and what happens if it is lost?
The Canadian and the US political systems each contain a Senate. In one of the regimes the Senate is the dominant chamber, in the other it is not. Identify which is which and explain why.
Provide a full description of the characteristics of a federal state. In your view, how would Plato and Aristotle classify this type of governmental system?
4.Above is 2 years and 4 months of actual demand data for a new call center. For example, cell
resenets 12,380 calls received in January 2019. Using this data, create two different models for demand forecasting. One combining Exponential Smoothing with Trend, and one combing Exponential Smoothing with both Trend and Seasonality. Ensure you conduct some type of error analysis and try to input adjust factors (such as Alpha) to minimize error. Please clearly indicate at the top of your sheet your selected value for factors (Alpha, Beta, Gamma) and the error analysis metric name and value. In the space below, indicate which model has less error and what you believe that indicates is true about the underlying demand pattern.
6.ou are a consultant who works for the Diligent Consulting Group. In this Case, you are engaged on a consulting
consulting basis by Loving Organic Foods. In order to get a better idea of what might have motivated customers’ buying habits you are asked to analyze the ages of the customers who have purchased organic foods over the past 3 months. Past research done by the Diligent Consulting Group has shown that different age groups buy certain products for different reasons. Loving Organic Foods has sent a survey to 200 customers who have previously purchased organic foods, and 124 customers have responded. The survey includes age data of past customers who purchased organic foods in the previous quarter.
Using Excel, create a frequency distribution (histogram) of the age data that was captured from the survey. You should consider the width of the age categories (e.g., 5 years, 10 years, or other). That is, which age category grouping provides the most useful information? Once you have created this histogram, determine the mean, median, and mode.
After you have reviewed the data, write a report to your boss that briefly describes the results that you obtained. Make a recommendation on how this data might be used for marketing purposes. Be sure to conduct adequate research on organic foods industry, organic market analysis, and healthy food industry using IBISWorld database or other databases such as Business Source Complete (EBSCO) and Business Source Complete - Business Searching Interface in our online library. Provide a brief description on the industry background and the consumer changing attitudes and behavior toward healthy lifestyles. Also identify the customer demographics of organic food industry and explain how the customers of Loving Organic Foods are different from this target market.
Data: Download the Excel-based data file with the age data of the 124 customers: Data chart for BUS520 Module 1 Case. Use these data in Excel to create your histogram.
Complete analysis in Excel using the Histogram function. Please watch the following video which covers how to create a histogram in Excel: https://www.youtube.com/watch?v=GL91GrVf3EY
If you are not so familiar with Excel, refer to the following link on Excel training videos: https://support.office.com/en-us/article/Excel-training-9bc05390-e94c-46af-a5b3-d7c22f6990bb?ui=en-US&rs=en-US&ad=US
Check the professional market research reports from the IBISWorld database to conduct the industry analysis. IBISWorld can be accessed in the Trident Online Library.
IBISWorld Overview (n.d.). IBISWorld, Inc., New York, NY.
IBISWorld Forecast (n.d.). IBISWorld, Inc., New York, NY.
IBISWorld Data and Sources (n.d.). IBISWorld, Inc., New York, NY.
IBISWorld Navigation Tips (n.d.). IBISWorld, Inc., New York, NY.
Length requirements: 4–5 pages minimum (not including Cover and Reference pages). NOTE: You must submit 4–5 pages of written discussion and analysis. This means that you should avoid use of tables and charts as “space fillers.”
Provide a brief introduction to/background of the problem.
Provide a brief description of organic food industry and target market characteristics such as their demographics, lifestyles and shopping behaviors.
Provide a written analysis that supports your Histogram age groups (bins).
Based on your analysis of the histogram data, provide complete and meaningful recommendations as the data relates to Loving Organic Foods’s marketing strategy.
Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size.
Have an introduction at the beginning to introduce the topics and use keywords as headings to organize the report.
Avoid redundancy and general statements such as "All organizations exist to make a profit." Make every sentence count.
Paraphrase the facts using your own words and ideas, employing quotes sparingly. Quotes, if absolutely necessary, should rarely exceed five words.
Upload both your written report and Excel file to the case 1 Dropbox.
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