Workshop 11 Slides - 16 October 2015 BUSS1020 Quantitative...

Info icon This preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
BUSS1020 Quantitative Business Analysis Workshop 11 Scott Liu 16 October 2015
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Aims § Use Excel and STATCRUNCH to produce scatter plots and be able to interpret these graphs. § Understand the concept of an explanatory (independent) variable and a response (dependent) variable. § Identify overall patterns showing the form (i.e. linear, quadratic, etc…), direction and strength of the relationship. § Calculate the correlation and interpret the answer in terms of strength and direction. § INTERPRET the following using the Excel output v Coefficients – interpret the estimates for the intercept and the slope coefficients. § Understand the relationships between coefficient, standard error, etc… in the Regression Table. § Interpret the following using the Excel and STATCRUNCH output v Coefficients – statistically and in practical terms v p-values v ࠵? " § Test whether an estimated coefficient is significant. § Use the p-values to make decisions on significance. § Explain the overall strength of fit of the model, using ࠵? " § Use residual plots to investigate the properties of the assumptions about the error term 2 Aims Lecture Recap Learning the Basics Applying the Techniques
Image of page 2
Regression Analysis: Introduction Aims Lecture Recap Learning the Basics Applying the Techniques 3 Correlation vs. Regression § Correlation : measures the strength of linear relationship between two variables. § Regression is used to predict the value of a dependent variable based on the value of at least one independent variable . This will explain the impact of changes in an independent variable on the dependent variable. v Dependent variable : variable we wish to predict or explain v Independent variable : variable used to predict or explain the dependent variable.
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern