The Artsy Corporation

Topics: Regression analysis, Statistics, Linear regression Pages: 14 (4934 words) Published: December 3, 2013
Table of Contents
Introduction___________________________________________________________3 PART 1: Descriptive Statistics__________________ __________________________5 Defining Important Terms_______________ ___________________________5 Data Analysis of Pay Rate________ _____________________________________6 Data Analysis of Pay Rate vs. Gender¬¬¬¬¬¬¬¬¬¬¬_______________________________________7 Data Analysis of Grade________________ ________________________________9 Data Analysis of Time within Grade_______________________________________11 PART 2: Regression Analysis____________________________________________ 12 Conclusion___________________________________________________________25 Glossary_____________________________________________________________26

Introduction
In the Arts Corporation Case, we are presented with a lawsuit put together by all female employees that work at Artsy Corporation. With this lawsuit the female part of the company tries to make a point that they have been discriminated in the workplace due to their gender. They make a statement that gender would affect certain factors such as: pay, hiring, promotions and other elements which are involved with the career of Artsy’s employees. This paper will put together statistical information and analysis based on the data we retrieve in order to give Artsy’s lawyers a perspective of what the company truly looks like in order for them to be able to put together a defense.

The data put together for us to analyze is based on the payroll of Artsy’s 256 employees at one of their facilities. This specific data was selected by usage of simple random sampling (the sample represents the population, i.e. every employee’s pay rate and working conditions).

The data includes:
an identification number (IDNUMBER) that would permit us to identify the person by name or social security number,

the person's sex (SEX) where a 0 denotes female and a 1 denotes a male,

the person's job grade in 1986 (GRADE), hierarchy level at company

the length of time (in years) the person had been in that job grade as of 12/31/86 (TING), and

The person's weekly pay rate as of 12/31/86 (RATE). (this being the most important point of concern)

In order to analyze this data statistically we will create multiple regression models. In this case, we will consider Pay Rate as a dependent variable and Gender, Job Grade and Time in Grade as independent variables. We will work through the data and try to find evidence to show whether or not gender plays a role in the company by influencing the salaries. On the other hand, if we find out that gender does not play a role in influencing the salary then we will try to find the other independent variable that does make a difference.


Part 1: Descriptive Statistics
Defining Important Terms
In this paper we will be making use of descriptive statistics which is basically a way of collecting, summarizing, and analyzing our data in order to come to a conclusion. This is very valuable for us since it will allow us to analyze of large group of numbers such as the set of data we are considering. When analyzing each specific set of data we will be considering both the central tendency and variation of the specific variable we are discussing.

Also in this paper we will refer to the “mean” in specific parts, where the word basically refers to a measure of central tendency, it is the arithmetic average of the numbers in our data. In order for our reader to have a better understanding of mean and arithmetic average, we have given an example below: By using our data and the software available to us, we were able to conclude that the average pay rate of females in Artsy Corporation was $833 per week, whereas the average pay rate of males in Artsy Corporation was $1128 per week. With this information we can have an idea that males have a higher salary (This is a quick example which...
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