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ACT362: Cost Accounting

Prepared for

Mokta Rani Sarker

Lecturer, School of Business

Prepared by

Md. Jahidujjaman ID # 09510190

Abdulla al baki ID#09310237

Mahamuda Islam ID: 09410097

Fatema Nelu ID# 10510238

University of Information Technology

& Sciences (UITS)

26th December 2011

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Introduction:

Generally Regression is a statistical tool to estimate or predict the unknown values of one variable from known values of another variable. On the other hand we can say that, Regression analysis is the statistical technique that identifies the relationship between two or more quantitative variables: a dependent variable, whose value is to be predicted, and an independent or explanatory variable (or variables), about which knowledge is available. The technique is used to find the equation that represents the relationship between the variables. A simple regression analysis can show that the relation between an independent variable X and a dependent variable Y is linear, using the simple linear regression equation Y= a + bX (where a and b are constants). Multiple regression will provide an equation that predicts one variable from two or more independent variables, Y= a + bX1+ cX2+ dX3.

An Important overview on regression analysis

Regression analysis includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the additional expectation of the dependent variable given the independent variables — that is, the average value of the dependent variable when the independent variables are held fixed. Less commonly, the focus is on a quintile, or other location parameter of the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function, which caconn be described by a probability distribution.

Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables

The performance of regression analysis methods in practice depends on the form of the data generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is in general not known, regression analysis often depends to some extent on making assumptions about this process. These assumptions are sometimes (but not always) testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally.

Background of apex food

Apex Foods Co., Ltd. is the subsidiary of Apex Group Co., Ltd. established in 1994. And under great effort of all staffs , Apex Foods Co., Ltd. was granted with GMP. We are determine to deliver the best standard of production by choosing good quality of raw materials and manufacturing all products in high hygienic rooms.

Furthermore, we have quality control in every process and provide training program for employee's hygienics in order to correspond to GMP system. As the result, our products have delivered top standard quality and met customers' expectations.

Company Determination

We have done market researches before designing and developing each item by professional team. Meanwhile, we are also importing goods from oversea. Our goal is to have the best selection for accomplishing the customers' satisfaction.

Awards

- GMP (Good Manufacturing Practice)

It is a set of regulations and guidelines controlling the quality of manufacturing operations aimed at ensuring consistency of product quality in order to

ensure patient safety.

- Halal

It means all food should be prepared, processed, packaged, transported and stored in such a manner.

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Product overview

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In October 2008, Apex Foods has signed the contract with Korea Trading Co., Ltd, (Korea) who will introduce Yofruit brand under Sanrio license in Korea. At the beginning, it comes up with Strawberry Yoghurt Flavor. More flavors will be introducing after all.

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As a custom food manufacturer, Apex Food specializes in the development and production of a wide variety of food products, including dips, dressings, soups, pastas, sauces, gravies, marinades, bastings, salsas, spice blends, seasonings, salads and processed vegetables and cooked items, to name a few. Our core competencies include research, recipe and product development, ingredient sourcing, custom-packaging and merchandising expertise in serving our grocery, foodservice, chain restaurant, wholesale-club, convenience store and institutional clients. As a multi-faceted manufacturer of food product, Apex Food supplies fresh, fresh-frozen and frozen foods, in a multitude of rigid and flexible packaging, as refrigerated and shelf-stable, according to client needs. Flexible, service-driven, with a proven record of performance, we blend our experience and industry knowledge with professional expertise and advanced technology, to deliver successful food solutions for the clients we serve.

Cost of goods sold

Cost of goods sold (COGS) refers to the inventory costs of those goods a business has sold during a particular period. Costs are associated with particular goods using one of several formulas, including specific identification, first-in first-out (FIFO), or average cost. Costs include all costs of purchase, costs of conversion and other costs incurred in bringing the inventories to their present location and condition. Costs of goods made by the business include material, labor, and allocated overhead. The costs of those goods not yet sold are deferred as costs of inventory until the inventory is sold or written down in value.

Components of cost of goods sold

The cost of goods produced in the business should include all costs of production. The key components of cost generally include:

• Parts, raw materials and supplies used,

• Labor, including associated costs such as payroll taxes and benefits, and

• Overhead of the business allocable to production.

Direct Materials

All of the materials that go into making a product are called "Raw Materials."  Raw materials come in two flavors: Direct Materials and Indirect Materials.  

Direct materials are the raw materials that become part of the product.  For example, bricks, shingles, and bath tubs would be the direct materials when building a house.  Paper would be a direct material when making grocery bags.  Seems easy, but there is a catch.

Direct Labor

The definition of direct labor is pretty easy.  Direct labor represents the people who do the core work of the business.  For example, if the business is a construction company, direct labor would be the people actually constructing the building.  They would be the people with hammers and saws in their hands.  In a retail store, direct labor would be the people helping on the sales floor doing the basic work that takes place serving the customers.  In a grocery bag factory, direct labor are the people running the machines actually making the bags.  I think of direct labor as the people who make or build the product.

Factory Overhead

The definition for overhead is easy.  Here it is......

If a cost is not direct labor or direct materials, the cost is overhead.

In other words, overhead is a multitude of different costs including indirect labor and indirect materials.  Here are a few of many examples: electricity, property taxes, advertising, accounting, janitors, cleaning supplies, distribution costs, legal fees, interest, inspectors, human resources department, etc, etc, etc.

Life would be too easy if it were just that simple.  There is one wrinkle.  There is a distinction between between overhead and manufacturing overhead.

Regression Analysis

|Variables Entered/Removed(b) |

|Model |Variables Entered |Variables Removed |Method |

|1 |Factory Overhead, Direct Labor, Direct Materials(a) |. |Enter |

|a All requested variables entered. |

|b Dependent Variable: Cost of Production |

|Model Summary |

|Model |

|ANOVA(b) |

|Model |

|b Dependent Variable: Cost of Production |

|Coefficients(a) |

| |

Interpretation of output summary

The regression model like that,

Here, Y= Cost of production

A= Constant

b1,b2 &b3= Regression coefficient

X1= Direct Materials

X2 = Direct Labor

X3= Factory overhead

From the co-efficient table, the values of a, b1,b2& b3 are found out & the regression model can be written as follows:

Y= a+b1x1+b2x2+b3x3

= -6537089.828+.248x1+38.489x2+12.326x3

This equation indicates that if taka of direct materials increases by 1taka, the cost production will increases by .248 taka and other things remain constant.

Again, if taka of direct labor increases by 1 taka, the cost of production will increases by 38.489 taka and other things remain constant.

On the other hand, if taka of factory overhead increases by 1taka, the cost of production will increases by 12.326 taka and other things remain constant.

The relationship among the variables in relative term

The relationship among the variables in relative terms can be estimated with the help of coefficient of correlation, (r).

r= .806 indicates that there exists a high degree of positive relationship among the variables.

Explanatory power of independents variables

The explanatory power of independents variables can be assessed with the help of coefficient of determination (r2 ).

r2= .650 indicates that 65.00% of the variations in cost of production can be explained by the variation of direct materials, direct labor and factory overhead .

.

Influencing power of independent variables

The influencing power of independent variable can be assessed with the help of of standardized Coefficient β(beta).

β (dm)=.610

β (dl)= .381

β (foh)=.356

βdm>βdL>βFOH

SO, it is evident that taka of direct materials has more influencing power than taka of direct labor and factory overhead , and also taka of direct labor has more influencing power than taka of factory overhead.

Significant of results or, model fitness

From the ANOVA ( analysis of variance) table, it is evedent that the results are statically insignificant because they are statically significant at .707 or 70.7% level which I higher than that of .05 or 5% level.

Measuring the significance of the coefficients

In the out put above we see that the t values are given for each of the variables. Besides this significance level for each t values are given in the model as well as.

And from the coefficient table , it is evident that b1, b2 &b3 are statistically insignificant because they are statistically significant at .696 or 69.6% another one .771 or 77.1% and, last one is .813 or 81.3% level respectively which higher than that of .05 or 5%.

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