Examine how the market structure impacts the company’s business strategy in each industry
Chapter 5
1. Discuss when you would use discriminant analysis instead of multiple regression analysis. Explain the difference between metric and nonmetric variables. (This is also discussed in Chapter 1.) Chapter 5 100 word minimum
In choosing an appropriate analytical technique, we sometimes encounter a problem that involves a categorical dependent variable and several metric independent variables. Recall that the single dependent variables in regression are the appropriate statistical techniques when the research problem involves a single categorical dependent variable and several metric independent variables. In many cases, the dependent variable consist of two groups or classifications, for example, male versus female, high verses low, or good versus bad. In other instances, more than two groups are involved, such as low, medium, and high classifications. Discriminant analysis and logistic regression are capable of handling either two groups or multiple (three or more) groups. The results of a discriminant analysis and logistic regression can assist in profiling the intergroup characteristics of the subjects and in assigning them to their appropriate groups.
2. Discuss the major issues relating to types of variables used and sample size required in the application of discriminant analysis. Chapter 5 100 word minimum.
To apply discriminant analysis, the researcher first must specify which variables are not to be independent measures and which variable is to be dependent measure. The researcher should focus on the dependent variable first. The number of dependent variable groups must be mutually exclusive and exhaustive. After a decision has been made on the dependent variable, the researcher must decide which independent variable to include in the analysis. Independent variables are selected in two ways: 1. By identifying variables either from previous research or from the theoretical model underlying the research question, and 2. By utilizing the
1. Discuss when you would use discriminant analysis instead of multiple regression analysis. Explain the difference between metric and nonmetric variables. (This is also discussed in Chapter 1.) Chapter 5 100 word minimum
In choosing an appropriate analytical technique, we sometimes encounter a problem that involves a categorical dependent variable and several metric independent variables. Recall that the single dependent variables in regression are the appropriate statistical techniques when the research problem involves a single categorical dependent variable and several metric independent variables. In many cases, the dependent variable consist of two groups or classifications, for example, male versus female, high verses low, or good versus bad. In other instances, more than two groups are involved, such as low, medium, and high classifications. Discriminant analysis and logistic regression are capable of handling either two groups or multiple (three or more) groups. The results of a discriminant analysis and logistic regression can assist in profiling the intergroup characteristics of the subjects and in assigning them to their appropriate groups.
2. Discuss the major issues relating to types of variables used and sample size required in the application of discriminant analysis. Chapter 5 100 word minimum.
To apply discriminant analysis, the researcher first must specify which variables are not to be independent measures and which variable is to be dependent measure. The researcher should focus on the dependent variable first. The number of dependent variable groups must be mutually exclusive and exhaustive. After a decision has been made on the dependent variable, the researcher must decide which independent variable to include in the analysis. Independent variables are selected in two ways: 1. By identifying variables either from previous research or from the theoretical model underlying the research question, and 2. By utilizing the