MKT 500 Chapter Notes - Chapter 14: Null Hypothesis, Statistical Significance

• School: Ryerson University
• Department: Marketing
• Course: MKT 500
• Professor: Julie Kellershohn

Document Summary

Associaive analyses: determine whether a stable relaionship exists between two variables. Levels: implies that the variable is either an interval or a raio scale. Labels: implies that the level of measurement is not scale, typically nominal. Oten provide insights that lead to understanding even though we do not know if there is a cause-and-efect relaionship. Direcion: knowing if the relaionship is posiive or negaive. Patern: knowing the general nature of the relaionship. Cross-tabulaion and the associated chi-square value are used to assess if a non-monotonic relaionship exists between to nominally scaled variables. Cross-tabulaion table: a table in which data is compared using a row and column format. Cross-tabulaion cell: the intersecion of a row and column. Frequencies table: contains raw numbers determined from the preliminary tabulaion. Raw percentages table: contains the percentages of the raw frequency numbers. Column percentages table: divides raw frequencies by its column total raw frequency: column cell percent =