MARK2054 final exam notes

MARK2054 final exam notes - To include results in the...

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Unformatted text preview: To include results in the report Descriptive • Descriptives aims to reflect the “pattern” of responses found in the sample collected...”the simple stuff” (mean, mode etc). Remember to include percentages.- Look at valid percent- Straight forward, interpret data In the report, you can write “ 50% of population does this, 20% does that” Crosstab with Chi-Squared Hypothesis example: H : There is no association between gender and modem speed H 1 : There is an association between gender and modem speed • Cross-tabulation allows you to examine two (or more) variables, and is used to assess whether there is an association/relationship between variables. • Tests the presence of an association between 2 nominal or ordinal variables • Reference percentages % not means The Chi-square test allows you to assess whether group or category membership on one variable is influenced by group or membership on another variable.- Again, like descriptives, simple and p ercentag es- However, significance (Pearson Chi-Squared line “Sig. 2 sided”) m ust b e < 0.05. higher, still m e ntion the p ercentag es but say “its not significant, and will not re further a n alysis- Look at bottom text-line. The % in brackets must be lower than 20%. If it is higher, mention that the results might be invalid and might require recoding. “20% of males did this, 30% of females did that” – compare One sample t-test “Used when there is data from a single sample of participants, to test assumptions about whether the mean of the population is the same as the hypothesised mean” To describe how the entire population thinks/behaves/responds with regards to one variable.- First time hypothesis is introduced. Include it in report, just state if null is reject (never “accept”)- In order to determine wheth er to reject/not reject null, we look at t stat OR p-va look at p-value). - If p value is < 0.05 (its significant), we DONT reject “This what bigger than that (quote m e a ns), a nd/but it was/wasn’t significance (quote p-valu reject/don’t reject null (state null)” Independent t-test Hypothesis example Ho → Null Hypothesis: on average, there is no difference in the importance males and females place on characteristics of an ISP H1 → alternate hypothesis: on average, there is a difference in the importance males and females place on characteristics of an ISP Similar to one-sample, except you’re now comparing a preference/behaviour between TWO (or more) different groups. If objective asks for “how do x and y differ in their...” Remember: Independent for 2 variables (gender), ANOVA for 3 (age) Paired t-test Same as One-sample/independent, except now you compare how the entire sample differ in two variables (difference to the responses to two separate questions)-...
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This note was uploaded on 07/17/2011 for the course MARK 2054 taught by Professor Mark during the Three '10 term at University of New South Wales.

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MARK2054 final exam notes - To include results in the...

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