ENFE 7027 HomeWork #2 DUE 07/18/22 Hypothesis testing While you can discuss the homework with other students, you must submit your work individually and it should reflect your own thinking and...

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I need questions 4-14 done for me please. i already completed 1-3.


ENFE 7027 HomeWork #2 DUE 07/18/22 Hypothesis testing While you can discuss the homework with other students, you must submit your work individually and it should reflect your own thinking and understanding of the questions. Do not type up the answers as a group, do it individually, using your own wording. 1. Explain the difference between null hypothesis and alternative hypothesis. Provide an example of a research question and the two types of hypotheses. Null and alternative hypotheses are both used in statistical hypothesis testing. The null hypothesis of a test always predicts no effect or no relationship between the variables. On the other hand, the alternative hypothesis states your research prediction of an effect or relationship. Null Hypothesis: On the average, the dosage sold under this brand is 50 mg(population mean dosage=50 mg). Alternative Hypothesis: On the average, the dosage sold under this brand is not 50 mg (population mean dosage does not equal to 50 mg). 2. What is the purpose of hypothesis testing in research and evidence-based practice? Provide an example of the application of hypothesis testing in evidence-based practice. Hypothesis testing is the process used to evaluate the strength of evidence from the sample and provide a framework for making determinations related to the population. An example of hypothesis testing would be null hypothesis- children who take vitamin C are no less likely to become ill during flu season. The alternative hypothesis would be children who take vitamin C are less likely to become ill during flu season. 3. What does the p-value mean? Is this an established benchmark used or an arbitrary number identified by researchers? The p-value, or the probability value is a number describing how likely it is that your data would have occurred by random chance (testing if the null hypothesis is true). Despite the general acceptance of the 0.05 cut-off for statistical significance, the p-value is ultimately an arbitrary value that has no more or less real-life importance than 0.049 or 0.051. Although as a community, science has operated with the perception that a p-value can add a sense of certainty to a finding. 4. A researcher designs a cohort study to estimate the risk of 30-day readmission after knee arthroplasty in Puerto Rico. She wants to find out if patients who received spinal anesthesia have lower risk of readmission compared to patients who received general/other anesthesia. Patients were followed 30 days after surgery to determine readmission. The researcher identified 78 patients who met the inclusion criteria for the study and followed them. She found a Relative Risk of 0.65 [0.51-0.81] comparing those with spinal anesthesia to those with general/other. a. Identify and explain your reasoning for the following concepts: i. Research Question ii. Independent variable and level of measurement iii. Dependent variable and level of measurement iv. Possible confounding variable v. Null hypothesis vi. Alternative Hypothesis vii. Effect Size (explain how the researcher calculated the effect size) b. What could be another method to calculate the effect size in this study? c. What are the established levels of effect sizes mentioned in the textbook? d. Based on the level of measurements identified for the independent and dependent variables, what would be the recommended statistical test? e. Explain what represents the type I and type II error in this example. Apply the errors to the practical exercise using the variables identified. 5. True or False: obtaining a statistically significant p-value (i.e., p< a prespecified level such as .05) is enough to conclude that there is a meaningful effect. 6. identified what indicators are used and interpret them in the case study presented in page 152. 7. explain pearson’s (r) correlation coefficient 8. what is the difference between pearson’s and spearmans’ rho? 9. covariance is a measure of relationships, but it is treated as a crude measure of relationships when compared with correlation. why is this? 10. what are the components of the linear regression equation? explain each variable in the equation. 11. mention the assumptions for a linear regression model. 12. in the table presented in the textbook, what does the “sig” column mean? interpret the confidence intervals for the estimate of “60.84”. 13. what is the difference between linear regression and multiple linear regression? 14. when is a logistic regression the best choice for modeling associations? what are the model parameters and assumptions? 1 a="" prespecified="" level="" such="" as="" .05)="" is="" enough="" to="" conclude="" that="" there="" is="" a="" meaningful="" effect.="" 6.="" identified="" what="" indicators="" are="" used="" and="" interpret="" them="" in="" the="" case="" study="" presented="" in="" page="" 152.="" 7.="" explain="" pearson’s="" (r)="" correlation="" coefficient="" 8.="" what="" is="" the="" difference="" between="" pearson’s="" and="" spearmans’="" rho?="" 9.="" covariance="" is="" a="" measure="" of="" relationships,="" but="" it="" is="" treated="" as="" a="" crude="" measure="" of="" relationships="" when="" compared="" with="" correlation.="" why="" is="" this?="" 10.="" what="" are="" the="" components="" of="" the="" linear="" regression="" equation?="" explain="" each="" variable="" in="" the="" equation.="" 11.="" mention="" the="" assumptions="" for="" a="" linear="" regression="" model.="" 12.="" in="" the="" table="" presented="" in="" the="" textbook,="" what="" does="" the="" “sig”="" column="" mean?="" interpret="" the="" confidence="" intervals="" for="" the="" estimate="" of="" “60.84”.="" 13.="" what="" is="" the="" difference="" between="" linear="" regression="" and="" multiple="" linear="" regression?="" 14.="" when="" is="" a="" logistic="" regression="" the="" best="" choice="" for="" modeling="" associations?="" what="" are="" the="" model="" parameters="" and="" assumptions?="">
Answered 1 days AfterJul 16, 2022

Answer To: ENFE 7027 HomeWork #2 DUE 07/18/22 Hypothesis testing While you can discuss the homework with other...

S answered on Jul 18 2022
72 Votes
4.
a)
i. The research question of the study is to find out whether the patients who received spinal anesthesia have lower risk of 30-day readmission after knee arthroplasty compared to patients who received general/other anesthesia.
ii. Anesthesia received : Spinal Anesthesia or General/other Anesthesia
Lev
el of Measurement: Nominal
iii. Readmission days
Level of Measurement: Ratio
iv. Gender can be a confounding variable since the dosage of Anesthesia will be change according to Gender.
v. The null hypothesis can be stated as:
H0: Patients who received spinal anesthesia have the same risk of readmission compared to patients who received general/other anesthesia.
vi. The alternative hypothesis can be stated as:
H1: Patients who received spinal anesthesia have the lower risk of readmission compared to patients who received general/other anesthesia.
vii. The effect size of the study reported in terms of relative risk. RR = 0.65
The relative risk can be calculated using the formula,
    Predictor
    Outcome
    
    Yes
    No
    Yes
    A
    b
    No
    C
    d
b) Cohen’s d method can also be used to find the effect size of the study .It can be calculated by the difference in means of two populations divided with standard deviation of the data.
i.e.
where s is the standard deviation of either the group when the variances of two groups are equal. When the variances of the two groups are not equal the pooled standard deviation (s) can be found out as,
So, here the difference of mean readmission days in two groups of patients received spinal anesthesia and of patients received general/other anesthesia is divided by the standard deviation to find out the effect size.
c)
1) Cohen’s d
It can be calculated by the difference in means of two populations divided with standard deviation of the data. i.e.
where s is the standard deviation of either the group when the variances of two groups are equal. When the variances of the two groups are not equal the pooled standard deviation (s) can be found out as,
A value of ±0.2 represents a small effect, ±0.5 represents a medium effect, and ±0.8 represents a large effect for Cohen’s d.
2) Pearson’s coefficient (r)
It can be found out by using the equation,
where t is the test statistic and df is the degrees of freedom
The value varies between −1 and +1, and the effect size is small if the value varies around 0.1, medium if the value varies around 0.3, and large if the value varies around 0.5.
3) ω2
The Omega squared is a measure of effect size that can be used in ANOVAs. It is an estimate that measures how much variation in the response variables are accounted for by the explanatory variables.
d) Independent sample t test will be recommended in which the mean readmission days will be compared in the two groups of patients who received spinal anesthesia and patients who received general/other anesthesia.
e) A Type I error is a false positive conclusion, in which the null hypothesis will be rejected when it is true. While a Type II error is a false negative conclusion in which it is failed to reject the null hypothesis...
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