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S519: Evaluation of Information Systems

S519: Evaluation of Information Systems. Social Statistics Inferential Statistics Chapter 12: Factor analysis. Last week. This week. When to analysis of variance with more than one factor Min and interaction effects ToolPak. Factorial analysis of variance.

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S519: Evaluation of Information Systems

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  1. S519: Evaluation of Information Systems Social Statistics Inferential Statistics Chapter 12: Factor analysis

  2. Last week

  3. This week • When to analysis of variance with more than one factor • Min and interaction effects • ToolPak

  4. Factorial analysis of variance • Proios, M. & Doganis, G. (2003). Experiences from active membership and participation in decision-making processes and age in moral reasoning and goal orientation of referees. Perceptual and Motor skills, 96(1), 113-126. • Two factors: age on moral reasoning and experience on decision-making • Three groups: • 56 who referee soccer; 55 who referee basketball; 37 who referee handball

  5. Factorial ANOVA • ANOVA: two-factor with replication • Change over time (Sep and June) and subject matter (math or spelling) – factorial analysis of variance • Test achievement (see Page 246) • ANOVA: two-factor without replication • Location of residence (urban or rural) and voting preference (green party or non-green party) • Test attitude toward environmental waste (see Page 246) • Excel does not provide support for ANOVA without replication.

  6. ANOVA: with replication • Figure 12.1

  7. Example • Two factors: gender (male or female) and treatment (high or low impact) • The same people experience both the high and low impact conditions

  8. Example • Three questions: • Is there a difference between the levels of impact (main effect)? • Is there a difference between the two levels of gender (main effect)? • What is the effect of difference levels of impact for males or females (interaction effects)

  9. Excel: Two-way ANOVA or factorial ANOVA

  10. Excel • Null hypothesis and research hypothesis

  11. Excel

  12. Excel • There is no main effect for treatment or gender (p=0.127, 0.176) • There is interaction effect (p=0.004) • It does not matter if you are in the high or low impact treatment group, or if you are male or female • It does matter if you are in both conditions simultaneously  the treatment does have an impact differentially on the weight loss of males than on females

  13. Exercise • S-p257 • 1 • 2 • 3

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