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Owner: statmath1
Created: Apr 18, 2018
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SMcDonald Project 2 Revison
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The survey conducted by Hosmer and Lemeshaw(2000), applied logistical regression collected at Baystate Medical Center. Data collected from one hundred and eighty-nine participants, of which categories were low birth weight and smoking to obtain a sample size.  Data was obtained from  Analysis: The measure of center had multiple modes to pull the data from, two of them were smoking versus non-smoking. Smoking weight categories were analyzed at 2000-2500 grams, Non-smoking analysis attributed to 3000-3500 grams. Smoking category had an outlier of less than 1000 grams, non-smoking category had no outliers.

The average weight by birth mothers, this key element gives a solid foundation for the study, given diet and birth weight of infants.  Data consisted from two variables, of which two were used for this project. To obtain an estimate of center, observations were assigned a numerical value to distinguish categories. These numerical identifiers are best suited by race, age, weight, smoke and environmental conditions.

The measure of center for data is roughly between 2777, and 3100 participants.  Having an even comparison, variables assures that the survey can have a good base of observations. Outliers consist of lower quartile of bracket (.500) given all conditions were met. Although the sample has a large measure of center,  variations had more of a spread , for instance one component of the survey is larger than the other. Variations in the median lie between 2000 -3100 grams. Non-smokers had a median of 3100, vs. smokers 2775.5 grams. A difference of 324.5 grams. 

 Low birth weight has been a concern for physicians for years. Data collected from Stat Crunch gave us an extensive quantitative observation by obtaining information from mothers checked into the medical center.  In comparison, qualitative examples include, smoke, race, uterine irritability. Invariably, data from observations concluded, first quartiles of 2495 observations; median of observations were 3100 observations; lastly the third quartile results were 3629 observations. This data was compiled from stat crunch web site and discusssed with topic concerning low birth weight, the students using the data are Sonya McDonald and Harriet Edmonds 

Summary of the data collected; Non-smokers 115; Smokers 74; total sample size of 189. The comparitive analysis, gives us data about the mothers weight during menses, and weight after giving birth. Data observed has a variance of 324.5 grams in weight  using  this comparitive study scientist,  use this as a predeterminant of infant birth weight. 



Result 1: Histogram   [Info]
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Result 2: Frequency Table   [Info]
Frequency table results for Bin(BWT):
Group: SMOKE=0
Count = 115
Bin(BWT)FrequencyRelative Frequency
1000 to 150030.026086957
1500 to 200080.069565217
2000 to 2500180.15652174
2500 to 3000220.19130435
3000 to 3500290.25217391
3500 to 4000270.23478261
4000 to 450060.052173913
4500 to 500020.017391304

Frequency table results for Bin(BWT):
Group: SMOKE=1
Count = 74
Bin(BWT)FrequencyRelative Frequency
500 to 100010.013513514
1000 to 150010.013513514
1500 to 200060.081081081
2000 to 2500220.2972973
2500 to 3000160.21621622
3000 to 3500170.22972973
3500 to 4000100.13513514
4000 to 450010.013513514

Result 3: Summary Stats   [Info]
Summary statistics for BWT:
Group by: SMOKE

Result 4: Boxplot   [Info]
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Result 5: Mean Median Mode   [Info]
Summary statistics for BWT:
Group by: SMOKE
SMOKEMeanMedianModeRangeStd. dev.
03054.95653100Multiple modes3969752.40901

Data set 1. Low Birth Weight Study   [Info]
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