ESP 178 Applied Research Methods. 2/26: Quantitative Analysis. Frequency distributions and graphs to show central tendency, variation, and skewness

Transcription

1 ESP 178 Applied Research Methods 2/26: Quantitative Analysis Key Concepts from Chapter 14 (Chapter 12 in Red Book): Descriptive Statistics Frequency distributions and graphs to show central tendency, variation, and skewness Purpose Measure Variable Type Definition Measures of Mode Best for nominal Most frequent value central Median Ordinal, interval, ratio Position average the midpoint Mean Interval, ratio Arithmetic average tendency (sometimes ordinal) Measures of Range Interval, ratio Highest value lowest value + 1 variation (sometimes ordinal) Variance Interval, ratio Average squared deviation of each case from the (sometimes ordinal) mean Standard deviation Interval, ratio (sometimes ordinal) Square root of the variance Associations Between One or More Variables p-value: Probability that the association is due to chance; goal is p-values less than 0.05 (5% significance level) or 0.01 (1% significance level). Independent Variable Nominal or Ordinal Ratio or interval Dependent Variable Nominal or ordinal Crosstabulation with Chi-square test Logistic regression Other forms of modeling Ratio or interval Difference of means with t-test (if 2 categories) Analysis of Variance (ANOVA) with F-test (if multiple categories Correlation coefficient Linear regression Other forms of modeling Chi-square: Compares expected frequencies in cells to observed frequencies in cells F-statistic: Compares variation between groups to variation within groups Multivariate analysis: Allows us to test causal hypothesis with non-experimental data by testing for relationship between independent and dependent variables while controlling for other variables that might cause a spurious relationship. Ethical issues: guidelines for graphs (pg. 377) Readings for 2/27: See if you can understand tables on the following pages of the reader: pg. 56 (Tables 2 through 4) from Gaterslaben; pg. 101 (Table 3) from Grob; pg. 27 (Table 2) and pg. 28 (Table 4) from Staats. Bring 3 copies of your draft survey to section on Thursday! Remember to meet in 1137 PES on Thursday!

2 Frequencies - Number of Times Children Played Outside in Last 7 Days Statistics N Valid 389 Missing 10 Mean 2.81 Median 2.00 Mode 0 Std. Deviation Variance Percentiles Frequency Percent Valid Percent Cumulative Percent Valid Total Missing System Total Histogram Frequency Mean = 2.81 Std. Dev. = N = 389 2

3 Frequencies - Whether or Not Children Played Outside in Last 7 Days Statistics N Valid 389 Missing 10 Mean.7147 Median Mode 1.00 Std. Deviation Variance.204 Percentiles Frequency Percent Valid Percent Cumulative Percent Valid Total Missing System Total Histogram Frequency Mean = Std. Dev. = N =

4 Crosstabs - Cul-de-sac or Not vs. Played Outside or Not Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent * % % % * Crosstabulation Total Total Count % within 32.5% 23.7% 29.8% Count % within 67.5% 76.3% 70.2% Count % within 100.0% 100.0% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 3.002(b) Continuity Correction(a) Likelihood Ratio Fisher's Exact Test Linear-by-Linear Association N of Valid Cases 373 a Computed only for a 2x2 table b 0 cells (.0%) have expected count less than 5. The minimum expected count is

5 Oneway ANOVA - Times Playing Outside by Cul-de-Sac or Not Descriptives 95% Confidence Interval for Mean N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum Total ANOVA Sum of Squares df Mean Square F Sig. Between Groups Within Groups Total Oneway ANOVA - Times Playing Outside vs. Cul-de-sac score (1 to 4 scale) Descriptives 95% Confidence Interval for Mean N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum Total ANOVA Sum of Squares df Mean Square F Sig. Between Groups Within Groups Total

6 Regression - Times Playing Outside as Dependent Variable Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1.361(a) a Predictors: (Constant), Q I. #9 - Nbrs Active Outside, #8 - Current Total Income,, presence of related kids <=5 current, Work or not current, Q I. #9 - Low Traffic, Q I. #9 - Low Crime, Q I. #9 - Nbr Interaction, presence of related kids <=12 current, Q I. #9 - Safe for Kids ANOVA(b) Model 1 Sum of Squares df Mean Square F Sig. Regressio n (a) Residual Total a Predictors: (Constant), Q I. #9 - Nbrs Active Outside, #8 - Current Total Income,, presence of related kids <=5 current, Work or not current, Q I. #9 - Low Traffic, Q I. #9 - Low Crime, Q I. #9 - Nbr Interaction, presence of related kids <=12 current, Q I. #9 - Safe for Kids b Dependent Variable: Coefficients(a) Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) Work or not current #8 - Current Total Income presence of related kids <= current presence of related kids <= current Q I. #9 - Safe for Kids Q I. #9 - Low Traffic Q I. #9 - Low Crime Q I. #9 - Nbr Interaction Q I. #9 - Nbrs Active Outside a Dependent Variable: 6