HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 3

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HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 3 Health surveys are commonly conducted to evaluate the overall state of affairs in terms of health decisions and trends. Often, the data collected are paired with other extant data in order to see if relationships exist that were not specifically studied or around which data were not specifically collected. The Centers for Disease Control, of course, collect thousands of data elements from a variety of health settings and surveys. The data set attached, “Case Study 3 – States.csv” includes 6 variables: • Food hardship rate – the reported rate of persons that experience the inability to purchase the food they need at least once in the last 12 months; • Obesity rate – the rate of obese persons, which is defined as having a BMI of 30 or greater; • Adult cigarette use – the proportion of persons 16 or older smoking more than 100 cigarettes in their lifetime and who continue to smoke; • Child cigarette use – the proportion of persons under 16 smoking more than 100 cigarettes in their lifetime and who continue to smoke; • Tax – the number of cents of state tax levied on a pack of 20 cigarettes; and • Location – the geographical location in the US to which each state and US is a member. 1. Create a scatterplot of the data for Food Hardship Rate and Obesity Rate. Copy the scatterplot into this document with axes and chart titles and interpret what the scatterplot tells us about the relationship between the two variables. 2. For the food hardship and obesity variables, determine the strength of any correlation, and determine whether it is significant at 0.05. Interpret the meaning of the correlation coefficient. A quick p-value calculator for Pearson correlation can be found on Social Science Statistics website (https://www.socscistatistics.com/pvalues/pearsondistribution.aspx). Write a journal entry for the results. 3. For the adult smoking and child smoking variables, determine the strength of any correlation, and determine whether it is significant at 0.05. Interpret the meaning of the correlation coefficient. A quick pvalue calculator for Pearson correlation can be found at https://www.socscistatistics.com/pvalues/pearsondistribution.aspx. Write a journal entry for the results. 4. One method of decreasing the smoking rate is to increase the tax rate on a pack of cigarettes. Using the mean of the adult and child rate for each state and DC, consider predicting the smoking rate from the tax rate. a) Calculate the mean of the adult and child smoking rates for each state and DC – insert this in an Excel column. b) With tax rate as the predictor variable, conduct a simple linear regression analysis on the data for mean adult and child smoking rate. In the analysis, you would typically report: 1 HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 3 • • • • • A regression plot analysis A statement and interpretation of the significance The regression equation and its meaning A statement and interpretation of R2 Practical statement of meaningfulness 5) Researchers attempt to see if there are relationships between variables that are not scale in nature, as well. In this case, we have 6 categories of “Location.” A bar chart showing the number of smokers in a random sample of 1000 residents in each region is shown below. Smokers 250 200 194 203 196 180 168 164 150 100 50 0 Mid-Atlantic Midwest Northeast South Southwest West Smokers a. Determine the number in each 1000 resident sample that are nonsmokers. b. Using the chi-square test for independence, determine whether or not the number of smokers in a region is independent of the region. • Indicate the null and alternate hypotheses. • Use the calculator at http://turner.faculty.swau.edu/mathematics/math241/materials/contablecal c/entry.php to conduct the chi-square test at 0.05. • Interpret the results and write a journal entry for the results. 2 HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 3 3 StateName State DistrictofColumbia DC Maryland MD Pennsylvania PA Virginia VA WestVirginiaWV NorthCarolina NC SouthCarolina SC Missouri MO Montana MT Nebraska NE Wisconsin WI Illinois IL Indiana IN Iowa IA Kansas KS Michigan MI Ohio OH Kentucky KY ConnecticutCT Delaware DE Maine ME Massachusetts MA NewHampshire NH NewJersey NJ NewYork NY RhodeIslandRI Vermont VT Alabama AL Arkansas AR Florida FL Georgia GA Louisiana LA Mississippi MS Oklahoma OK Tennessee TN Texas TX Utah UT Colorado CO Arizona AZ California CA Hawaii HI Nevada NV NewMexicoNM Minnesota MN NorthDakotaND SouthDakota SD FoodHardshipRate ObesityRateAdultCigaretteUse YouthCigaretteUse TaxCentsPerPack Location 0.163 0.237 153 207 250 Mid-Atlantic 0.163 0.283 152 119 200 Mid-Atlantic 0.15 0.286 202 184 160 Mid-Atlantic 0.166 0.292 190 243 30 Mid-Atlantic 0.225 0.324 256 218 55 Mid-Atlantic 0.211 0.291 203 177 45 Mid-Atlantic 0.219 0.308 204 205 7 Mid-Atlantic 0.195 0.303 231 189 17 Midwest 0.154 0.246 168 187 170 Midwest 0.144 0.284 167 183 64 Midwest 0.137 0.277 188 169 252 Midwest 0.175 0.271 186 181 98 Midwest 0.203 0.308 231 235 99.5 Midwest 0.155 0.29 172 200 136 Midwest 0.149 0.296 178 169 79 Midwest 0.181 0.313 196 188 200 Midwest 0.198 0.296 203 167 125 Midwest 0.223 0.304 256 261 60 Midwest 0.14 0.245 154 178 300 Northeast 0.21 0.288 183 190 160 Northeast 0.167 0.278 173 181 200 Northeast 0.145 0.227 150 160 251 Northeast 0.152 0.262 158 208 178 Northeast 0.158 0.237 158 170 270 Northeast 0.176 0.245 180 148 275 Northeast 0.181 0.254 151 133 346 Northeast 0.16 0.254 171 176 224 Northeast 0.234 0.32 225 208 42.5 South 0.211 0.309 215 203 115 South 0.216 0.266 171 161 133.9 South 0.217 0.28 177 169 37 South 0.213 0.334 221 176 36 South 0.245 0.349 233 196 68 South 0.213 0.311 255 226 103 South 0.217 0.292 220 209 62 South 0.216 0.304 179 212 141 South 0.177 0.244 98 85 69.5 Southwest 0.16 0.207 171 177 84 Southwest 0.205 0.247 161 197 200 Southwest 0.193 0.238 129 145 87 Southwest 0.118 0.218 154 152 260 Southwest 0.2 0.245 220 170 80 Southwest 0.181 0.263 179 240 91 Southwest 0.126 0.257 168 187 156 West 0.1 0.278 186 224 44 West 0.152 0.281 175 232 153 West Wyoming WY Idaho ID Alaska AK Oregon OR WashingtonWA 0.147 0.189 0.182 0.18 0.164 0.25 0.27 0.274 0.267 0.265 199 163 206 179 149 221 145 157 171 125 60 57 200 118 302.5 West West West West West Smokers Mid-Atlantic 194 Midwest 196 Northeast 168 South 203 Southwest 163 West 180 250 200 194 196 Mid-Atlantic Midwest 150 100 50 0 Smokers 203 196 180 168 Midwest Northeast 163 South Southwest West
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Running head: HAP 602

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HAP 602: Statistics for Health Services Management
Student's Name
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HAP 602

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HAP 602: Statistics for Health Services Management

ObesityRate against FoodHardshipRate
0.4
0.35

ObesityRate

0.3
0.25
ObesityRate against
FoodHardshipRate

0.2
y = 0.5454x + 0.1779
R² = 0.3371

0.15

Linear (ObesityRate against
FoodHardshipRate)

0.1
0.05
0
0

0.05

0.1

0.15

0.2

0.25

0.3

FoodHardshipRate

1.
FoodHardshipRate and ObesityRate are highly dependent on each other. The scatter
points appear close to each which implies that their relationship is directly proportional.
2. R2 = 0.3371
R = √0.3371 ≈ 0.5806 to 4 significant figures
𝛼 = 0.05
The p-value derived from the Social Science Statistics website is < 0.00001 and the
result is significant at p < 0.05. FoodHardshipRate and ObesityRate are moderately
and positively correlated. FoodHardshipRate has a significant effect on ObesityRate.
3. The value for r from excel is ~0.6183. Feeding these results into the website gives
the p-value as < 0.00001 and the result is significant at p < 0.05. The value of r

HAP 602

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indicates that adult smoking and child smoking are moderately and positively
correlated. Adult smoking has a significant effect on child smoking.

4. R2 (coefficient of determination) = 0.2312 = 23.12%. The model is no adequate to
predict the effect of an increase in the tax rate on cigarette smoking. The regression
equation is y = -1.394x + 394.08. F-computed = 14.73648 while Significance F is
0.000355. Since the significance F < F-computed, we reject the hypothesis that an
increase in the tax rates for cigarette packs will reduce ...


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