give a brief summary of the article, including hypotheses, methods, and findings

give a brief summary
of the article, including hypotheses, methods, and findings. Research the topic
and available data sources. On the basis of the biostatistical methods
discussed in the course (BELOW), analyze the article and its
findings. Write a 7 –10-page, double-spaced paper in Word format.
Apply APA standards to citation of sources. Utilize at least 7 scholarly sources
Here are some points to
consider in your analysis:
What data
are available on this topic?
What data
does the article use?
Discuss the level of measurement, assumptions that
can be made, statistics that can be calculated from these data, and the
general quality of the data.
What is the
type of study or study design used?
Explain the type of biostatistical study design that
the author has used.
Describe the hypothesis or hypotheses that the
author intends to test.
Explain the statistics that the author uses to test
these hypotheses.
What are
the article’s statistical findings?
Describe the statistical results of the author’s
analysis.
Provide a substantive interpretation of these
findings (What do the results mean in relation to the hypotheses and the
public health topic?).
Describe the author’s recommendations about this
topic based on his or her findings and hypotheses.
If you had
been the author, what changes, if any, would you have made in the study
you analyzed?
Discuss whether the author made any statistical
errors.
Were the
correct data used for the questions asked?
Were the
correct data available?
Were the
correct statistics used for the data available?
What other
data might you want to collect and why?
Do the
statistical findings support the author’s conclusions?
ARTICLE: Implementation of a prediabetes identification algorithm for
overweight and obese Veterans (ATTACHED)
BIOSTATISTICAL METHODS
inferential statistics (
parameter estimation and hypothesis testing).
estimation and hypothesis
testing for a mean.
hypothesis testing for a
mean for one-sample and two-sample scenarios. assumptions necessary for hypothesis
testing, study confidence interval methods, and practice biostatistical
problem-solving skills by calculating one-sample and two-sample t-tests and
confidence intervals based on a public health scenario. Performing hypothesis testing with one-sample
and two-sample inferences. Calculating
and interpret dependent and independent t-tests.
Identifing relationships
between confidence intervals and hypothesis testing.
nonparametric statistics vs parametric statistics.
levels of measurement of data and the effect of the level
of data on the choice of parametric or nonparametric statistics. *biostatistical
problem-solving skills by calculating a Wilcoxon rank-sum test to test the null
hypothesis..
levels of data measurement and parametric versus
nonparametric statistical methods.
types of data that require parametric methods and the
types of data that require nonparametric methods.
the advantages and disadvantages of using each method.
Categorical data can be measured as an ordinal variable or
nominal variable.
hypothesis testing using categorical data.
contingency tables as a way of representing relationships
between categorical data and the statistics used to test hypotheses
categorical data, contingency tables, chi-square and
Fisher’s exact test (FET)
correlation and regression methods. correlation
coefficient (R2) statistic in regression analysis and least squares regression
analysis
Pearson’s correlation coefficient, ANOVA, Least squares
regression analysis
multisample inference and the design and analysis of
epidemiological studies.
odds ratios (OR) and risk ratios (RR). https://homeworkvendors.comOrder Your Paper Online. Get an Expert Writer to Write your Paper