1. The data in BUSI1013 Credit Card Balance.xlsx is collected for building a regression model to predict credit card balance of retail banking customers in a Canadian bank. Use this data to perform a simple regression analysis between Account balance and Income (in thousands). (12 points)
2. Develop a scatter diagram using Account Balance as the dependent variable y and Income as the independent variable x.
3. Develop the estimated regression equation.
4. Use the estimated regression equation to predict the Account Balance of a customer with Income of $58 thousands.
5. Use the critical-value approach to perform an F test for the significance of the linear relationship between account balance and Income at the 0.05 level of significance.
6. What percentage of the variability of Account Balance can be explained by its linear relationship with Income?
7. Use the p-value approach to perform a t test for the significance of the linear relationship between Account Balance and Income at the 0.05 level of significance.

1. The data in BUSI1013 Credit Card Balance.xlsx is collected for building a regression model to predict credit card balance of retail banking customers in a Canadian bank. Use this data to perform a simple regression analysis between Account balance and Income (in thousands). (12 points)
   
2. Develop a scatter diagram using Account Balance as the dependent variable y and Income as the independent variable x.
3. Develop the estimated regression equation.
4. Use the estimated regression equation to predict the Account Balance of a customer with Income of $58 thousands.
5. Use the critical-value approach to perform an F test for the significance of the linear relationship between account balance and Income at the 0.05 level of significance.
6. What percentage of the variability of Account Balance can be explained by its linear relationship with Income?
7. Use the p-value approach to perform a t test for the significance of the linear relationship between Account Balance and Income at the 0.05 level of significance.

Use the following data to calculate and record the correlation coefficient, r.

To test whether the mean time needed to mix a batch of material is the same for machines produced by three manufacturers, the Jacobs Chemical Company obtained the following data on the time (in minutes) needed to mix the material.

a. Use these data to test whether the population mean times for mixing a batch of material differ for the three manufacturers. Use a=0.05.

Compute the values below (to 2 decimals, if necessary).

Calculate the value of the test statistic (to 2 decimals).

___________

The p value is (less than .01, between .01 and .025, between .025 and .05, between .05 and .10, greater than .10)

What is your conclusion?

________ (Conclude the mean time needed to mix a batch of material is not the same for all manufacturers, Do not reject the assumption that mean time needed to mix a batch of material is the same for all manufacturers)

b. At the a=0.05 level of significance, use Fisher's LSD procedure to test for the equality of the means for manufacturers 1 and 3.

Calculate Fisher's LSD Value (to 2 decimals).

___________

What is your conclusion about the mean time for manufacturer 1 and the mean time for manufacturer 3 ?

(These manufacturers have different mean times, Cannot conclude there is a difference in the mean time for these manufacturers)

A central air conditioning unit was installed on January 1, 2000 at an initial cost of
P650,000 and was expected to have a salvage value of P50,000 after a life of 7 years. a.
What amount of depreciation had accumulated in a sum-of-the-years’-digit method at the
end of 2003? b. Using the declining balance method, determine the depreciation charged
for 2004 and the book value at the end of 2004. c. If the equipment was sold on Jan 1,
2005 for P100,000, what amount of loss would result from this sale if sinking fund method
was being used with interest of 12% per year?

Show a complete and logical solution

An Analyst wants to know if there was a significance difference in the average of hours worked in a week from 2000 (Group 1) to 2004 (Group 2). He gathers all the data from the General Social Survey, and lists the following summary statistics from the sampling.

Source: General Social Survey (sda.berkeley.edu )

What is the correct null hypothesis?

Ho: mu2004-mu2000 < 0

Ho: mu2004-mu2000 does not equal 0

Ho: mu2000-mu2004 > 0

Ho: mu2004-mu2000 = 0

To study how social media may influence the products consumers​ buy, researchers collected the opening weekend box office revenue​ (in millions of​ dollars) for 23 recent movies and the social media message rate​ (average number of messages referring to the movie per​ hour). The data are available below. Conduct a complete simple linear regression analysis of the relationship between revenue​ (y) and message rate​ (x).

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Assignment specification — Case Study :IKEA Operations Management

IKEA is the one of the most successful furniture retailer globally. With 276 stores in 36 countries, they have managed to develop their own special way of selling furniture. Their stores’ layout means customers often spend two hours in the store – far longer than in rival furniture retailers. IKEA’s philosophy goes back to the original business, started in the 1950s in Sweden by Ingvar Kamprad. He built a showroom on the outskirts of Stockholm where land was cheap and simply displayed suppliers’ furniture as it would be in a domestic setting. Increasing sales soon allowed IKEA to start ordering its own self-designed products from local manufacturers. But it was innovation in its operations that dramatically reduced its selling costs. These included the idea of selling furniture as self-assembly flat packs, which reduced production and transport costs, and its ‘showroom-warehouse’ concept, which required customers to pick the furniture up them-selves from the warehouse (which reduced retailing costs). Both operating principles are still the basis of IKEA’s retail operations process today.

Stores are designed to facilitate the smooth flow of customers, from parking, moving through the store itself, to ordering and picking up goods. At the entrance to each store large notice boards provide advice to shoppers. For young children, there is a supervised children’s play area, a small cinema, and a parent and baby room so parents can leave their children in the supervised play area for a time. Parents are recalled via the loudspeaker system if the child has any problems. IKEA ‘allow customers to make up their minds in their own time’ but ‘information points’ have staff who can help. All furniture carries a ticket with a code number which indicates its location in the warehouse. (For larger items customers go to the information desks for assistance.) There is also an area where smaller items are displayed, and can be picked directly. Customers then pass through the warehouse where they pick up the items viewed in the showroom. Finally, customers pay at the checkouts, where a ramped conveyor belt moves purchases up to the checkout staff. The exit area has service points, and a loading area that allows customers to bring their cars from the car park and load their purchases. Behind the public face of IKEA’s huge stores is a complex worldwide network of suppliers, 1,300 direct suppliers, about 10,000 sub-suppliers, and wholesale and transport operations, including 26 distribution centres. This supply network is vitally important to IKEA. From purchasing raw materials, right through to finished products arriving in its

customers’ homes, IKEA relies on close partnerships with its suppliers to achieve both ongoing supply efficiency and new product development. However, IKEA closely controls all supply and development activities from IKEA’s hometown of Älmhult in Sweden. But success brings its own problems and some customers became increasingly frustrated with overcrowding and long waiting times. In response IKEA launched a programe ‘designing out’ the bottlenecks. The changes included:

• clearly marked in-store short cuts allowing those customers who just want to visit one area to avoid having to go through all the preceding areas;
• express checkout tills for customers with a bag only rather than a trolley;
• extra ‘help staff ’ at key points to help customers;
• redesign of the car parks, making them easier to navigate
• dropping the ban on taking trolleys out to the car parks for loading (originally implemented to stop vehicles being damaged);
• a new warehouse system to stop popular product lines running out during the day;
• more children’s play areas.

IKEA spokeswoman Nicki Craddock said: ‘We know people love our products but hate our shopping experience. We are being told that by customers every day, so we can’t afford not to make changes. We realized a lot of people took offence at being herded like sheep on the long route around stores. Now if you know what you are looking for and just want to get in, grab it and get out, you can.’ Operations management is a vital part of IKEA’s success IKEA shows how important operations management is for its own success and the success of any type of organization.

Of course, IKEA understands its market and its customers. But, just as important, it knows that the way it manages the network of operations that design, produce and deliver its products and services must be right for its market. No organization can survive in the long term if it cannot supply its customers effectively. And this is essentially what operations management is about – designing, producing and delivering products and services that satisfy market requirements. For any business, it is a vitally important activity. Consider just some of the activities that IKEA’s operations managers are involved in:

‑ Arranging the store’s layout to give a smooth and effective flow of customers (called process design).

‑ Designing stylish products that can be flat-packed efficiently (called product design).

‑ Making sure that all staff can contribute to the company’s success (called job design).

‑ Locating stores of an appropriate size in the most effective place (called supply network design).

‑ Arranging for the delivery of products to stores (called supply chain management).

‑ Coping with fluctuations in demand (called capacity management).

‑ Maintaining cleanliness and safety of storage areas (called failure prevention).

‑ Avoiding running out of products for sale (called inventory management).

‑ Monitoring and enhancing quality of service to customers (called quality management).

‑ Continually examining and improving operations practice (called operations improvement).

And these activities are only a small part of IKEA’s total operations management effort. But they do give an indication, first of how operations management should contribute to the business’s success, and second, what would happen if IKEA’s operations managers failed to be effective in carrying out any of its activities. Yet, although the relative importance of these activities will vary between different organizations, operations managers in all organizations will be making the same type of decision (even if what they decide is different).

Question:

1. What do you identify as the ‘operations function’ within IKEA? How is this different from the ‘sales function’?