Results_LAB_Spring_08-1 - Results Results BBH 310w Lab...

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Unformatted text preview: Results Results BBH 310w Lab Spring Semester 2008 Today’s Overview Today’s What is presented in a results section Examples Determining appropriate test Findings Writing-up findings in text Specific Questions Specific In the Results Section… In Statistical analysis described Results are presented but not interpreted Results not Tables and graphs will be described and Tables referenced Identify the results in their order of Identify importance or relevance importance State results in a clear and detailed manner State Present all necessary details (e.g., t-value Present and p-value, means & standard deviations) and In the Results Section (cont.)… In Present data quality measures Coefficient alpha Test-retest correlation Examples Examples Study 1 A study was performed to look at gender differences in daily calories from carbohydrates. Ninety men and women each completed a food diary and logged their calorie intake for one day. Study 1: Findings Study Mean calories Men = 750 (SD + 95) calories Men Women = 925 (SD + 110) calories t-test was performed and showed a t-test significant gender difference [t(88)=3.45, p<.01]. Study 1: Write-up Study The current study investigated gender The differences in daily calories from carbohydrates. Men consumed 750 calories from carbohydrates (SD + 95), while women consumed 925 calories from carbohydrates (SD + 110). An independent samples t-test confirmed that this difference was statistically significant [t(88) = 3.45, p<.01]. Study 1: Tables & Graphs Study Table 1. Mean and standard deviation for calorie consumption among men and women Men 750 + 95 Women 925 + 110 1100 1000 900 Mean Calories Consumed Mean ± SD (Calories) Figure 1. Mean and standard deviation for calorie consumption among men and women 800 700 600 500 400 300 200 100 0 Men Women Gender Examples (cont.) Examples Study 2 This study is about level of social support and depression (N=300). The support independent variable is social support independent with 3 levels: low, medium and high. The with dependent variable is the score on the depression measure (CESD) within the range of 0-60. Analysis of Variance (ANOVA) was performed on the data. Study 2: Findings Study The mean and standard deviation values The of depression for each group were: Low group Low Medium group High group High 10.0 ± 1.8 18.2 ± 1.5 12.0 ± 1.9 10.0 ± 1.8 10.0 ANOVA F-test showed that the groups ANOVA were significantly different from each other: F(2,297)=5.3, p<.01. Study 2: Write-up Study The current study examined whether level of The social support predicted depression. ANOVA was performed on the data and found that the groups were significantly different from each other [F(2, 297) = 5.3, p<0.01]. A post-hoc tother test revealed that the medium and high groups test were not different from one another [t(298)=1.4, p>0.05]. Mean (+SD) of depression scores p>0.05]. SD) were 18.2(+1.5), 12(+1.9) and 10(+1.8) for the were 1.8) low, medium and high groups respectively (see Figure 1). Study 2: Tables & Graphs Study Table 2. Mean and standard deviation for depression scores among participants with low, medium or high social support Figure 2. Mean and standard deviation for levels of depression among the participants with low, medium or high social support 22 20 Mean (± SD) Depression Scores Low 18.2 ± 1.5 Medium 12.0 ± 1.9 Mean Level of Depression 18 16 14 12 10 8 6 4 2 0 High 10.0 ± 1.8 Low Medium Social Support High Examples (cont.) Examples Study 3 A study was done to investigate the study association between number of cigarettes smoked per day and number of alcoholic drinks consumed per day. Three hundred daily smokers were surveyed. daily Study 3: Findings Study Mean of 20 cigarettes per day (SD + 6.5). Mean Range: 44 Range: Mean of 7.81 drinks per day (SD + 9.0). Mean Range = 23 Correlation analysis showed a strong Correlation positive correlation (r = +0.85, p<.001) between cigarettes per day and drinks per day. Study 3: Write-up Study The current study examined the relationship The between daily cigarette consumption and daily alcohol consumption. Three hundred daily smokers provided data. Subjects smoked a mean of 20 cigarettes per day (CPD) (SD + 6.5) and drank a mean of 7.81 drinks per day (DPD) (SD + 8.0). Range of values for CPD was 44, while the range for DPD was 23. Correlation analysis showed a strong positive correlation between showed cigarette and alcohol consumption (r = +0.85, cigarette p<.001) meaning that as cigarette use increased so did level of alcohol consumption. so Study 3: Tables & Graphs Study Table 3. Mean and standard deviation for amount of cigarettes and drinks consumed Figure 3. The correlation between number of drinks consumed and cigarettes smoked 26 24 22 Cigarettes Drinks 20 + 6.5 7.81 ± 8.0 18 N um ber of D r ink s Mean (± SD) 20 16 14 12 10 8 6 4 2 0 -5 0 5 10 15 20 25 Number of Cigarettes 30 35 40 45 ...
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This note was uploaded on 08/26/2009 for the course BB H 310W taught by Professor Saltsman,brian during the Spring '07 term at Pennsylvania State University, University Park.

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