Question

Important Note
For the remaining items you are to create an APA styled results presentation. This will include a table of results, and written inference and interpretation. If you are unclear about APA styled tables, review carefully the examples provided in the linked Word document on the Course Index. Each item is worth 10 points (unless specified otherwise) and will be graded according to the following rubric: Calculation Numeric Results 5 points, Written Presentation 2 points, and APA style 3 point.

6. Does climate predict suicide rates across the USA? According to Dixon and Kalkstein (2009) climate may be a predictor of suicide incidents. To test this possible link, data were collected on suicide rate per 100,000 individuals in each state and several indicators of climate. More specifically, the data include the following:
• Suicide rate per 100,000 individuals (i.e., 15 = 15 suicides out of 100,000 individuals)
• Average percentage of time the sun shines during the day (i.e., 58 = sun shines 58% of time during day on average)
• Average number of clear days (i.e., 99 = clear skies 99 out of 365 days a year)
• Average afternoon humidity (i.e., 52 = humidity is 52% on average at 4pm in the afternoon)
• Average temperature in Fahrenheit (i.e., 62.8 = average temperature throughout year is 62.8)
The data can be downloaded as either an SPSS file or Excel file. The variable names in each file are
• Suicide_Rate = Suicide rate per 100,000 individuals
• Percent_sun_days = Average percentage of time the sun shines during the day
• Number_clear_days = Average number of clear days
• Afternoon_humidity = Average afternoon humidity
• Average_Temp_F = Average temperature in Fahrenheit
SPSS data file: http://www.bwgriffin.com/gsu/courses/edur8131/data/test3_suicide_data.sav
Excel data file: http://www.bwgriffin.com/gsu/courses/edur8131/data/test3_suicide_data.xlsx
Is there any evidence that these four climate indicators statistically predict suicide rates? Use Regression for this analysis. (10 points)
Data sources for this item:
• Suicide data (2005 data): http://www.suicide.org/suicide-statistics.html#death-rates
• Dixon and Kalkstein (2009): http://geosciences.msstate.edu/faculty/dixon/reprints/2009compass.pdf
• Average humidity (14 June 2013): http://www.currentresults.com/Weather/US/annual-average-humidity-by-state.php
• Number of sunny days (14 June 2013): http://www.currentresults.com/Weather/US/average-annual-state-sunshine.php

Answer 1

Let, us take chi-square

To calculate the chi-square coefficient :

X² = (O_i –E_i)/ E_i

Oi is the observed value of the data in each cell

Ei is the expected value of the data in each cell

Ei (First cell) = 2229 * 1672 / 2542 = 1466.12

	Negative	Marijuana	Cocaine	Other Drugs	Row Totals
Male	1465  (1466.12)  [0.00]	146  (130.23)  [1.91]	33  (39.46)  [1.06]	28  (36.18)  [1.85]	1672
Female	764 (762.88) [0.00]	52 (67.77) [3.67]	27 (20.54) [2.04]	27 (18.82) [3.55]	870
Column Totals	2229	198	60	55	2542

                                                     Chi-square table

1.A chi-square test of association was performed to examine the relation between gender and drug screening results

2.Null Hypothesis: Gender and the types of drug screening results didn’t associated

The expected values are shown in brackets in table

Chi-square coefficient = 0.00 + 0.00 + 1.91 + 3.67 + 1.06+ 2.04 + 1.85 + 3.55 = 14.08

                The p-value = 0.002

As p-value < 0.05, Reject the null hypothesis.

The relation between these variables was found to be significant,

X² (4, N = 2542) = 14.08, p = .002. The screening results differ by applicants' sex.

6. Does climate predict suicide rates across the USA? - NEED TABULAR FORM FOR CLARITY