Statistical Analysis Presentation
פרקים
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0:00פרק 1: Hello, Dr. 151s · Speaker 1
Hello, Dr. Thayer. I'm here to do a presentation on the numerical analysis module. The title of my presentation is about diabetes risk factors. I will look at the insights from the Pima Indian Diabetes Database. Before I do that, let me giv…
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2:32פרק 2: of diabetes across the world. 310s · Speaker 2
of diabetes across the world. Looking at this map here on the side, it's a map that estimates an increase on diabetes from 2019 to 2045. And then if you look at the world picture, it shows that between 2019 and 2025, there will be an increa…
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7:43פרק 3: These can be described as one of those values that are supposed to be carrying missing data in the dataset instead of being real pregnancies. 177s · Speaker 1
These can be described as one of those values that are supposed to be carrying missing data in the dataset instead of being real pregnancies. Glucose, values of zero and glucose, this is also not physiologically correct, and one cannot have…
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10:42פרק 4: which is lower than the 40-49 age group. 98s · Speaker 2
which is lower than the 40-49 age group. And in summary, one can say that the data highlights that diabetes risk increases significantly with age, particularly from the age status onwards, even though that the number of participants decline…
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12:21פרק 5: Diabetics, if it needs to be controlled, obesity and overweight must be taken into consideration. 81s · Speaker 1
Diabetics, if it needs to be controlled, obesity and overweight must be taken into consideration. Exploration of data statistics. Question 10 was also looking at diabetes rate across pregnancies. These are the categories for pregnancy count…
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13:43
Looking at the second question in terms of inferential statistics, the first one wanted us to test if there is a difference between glucose levels for those with and without diabetes. The null hypothesis says the mean glucose of those with …
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19:00
915, the degrees of freedom is 3, the p-value is far less than 0.5. Concluding on the results on this one for age group and outcome, the p-value is far below 0.5, meaning that the association between age group and diabetes outcome is statis…
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24:10פרק 8: This accounts for the very large number of predictors, those dummy variables for PMI. 311s · Speaker 2
This accounts for the very large number of predictors, those dummy variables for PMI. And then statistically, it explains that the model only explains about 44% of variance in the dataset. Question seven, in the inferential statistics, we w…
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29:23
with that odd ratio and that significance level this means that the odd ratio is extremely close to one and the the oval and it also the significance overlaps with one meaning that the interaction effect is negligent and is not significant …
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31:07
this they come that at light level bmi with the at that co deviance coefficients with that interaction with that p value And the odd ratio, this suggests that higher BMI increases diabetes odds by about 8% per unit, but the midpoint is a mi…
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33:05פרק 11: strong variable with precise effect. 75s · Speaker 1
strong variable with precise effect. That means glucose is the strong variable to predict. diabetes in the sample data set. Pregnancies with that odd ratio and that significance level, it means that it is a significant but meaningful variab…
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34:21פרק 12: Key findings that are found for diabetes risk from the analysis is prevalence. 128s · Speaker 3
Key findings that are found for diabetes risk from the analysis is prevalence. Total, summing up the results, the total of about 34.9 of participants are diagnosed with diabetes from the sample data set. Age, actually the increase in age ri…
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36:31פרק 13: impact beyond these risk factors that are identified here. 177s · Speaker 2
impact beyond these risk factors that are identified here. In recommendations, there are following recommendations that I'm putting forward based on the study that I did analyzing the PIMA dataset. One is to prioritize glucose monitoring. S…