Module 6 statistics part 2 Questions With Complete
Solutions
5. Which of the following best describes the correlation in the
scatterplot below?
Strong positive correlation
Strong negative correlation
Weak positive correlation
Weak negative correlation
swer is b. This scatterplot reveals a strong negative correlation.
A result is significant if it was likely caused by chance.
,True
False
ect
×
The answer is b. This statement is false. A result is significant if
it was unlikely to have been caused by chance.
A hypothesis test* A hypothesis test* will tell us whether the
results are statistically significant or not.
Estimate the correlation coefficient for the scatterplot in
question #5.
−0.92
−0.1
0.5
0.92
orrect
×
The answer is a. Weak correlations have correlation coefficients
close to 0. Because this is a strong negative correlation, the
correlation coefficient is negative and close to −1, so it can be
estimated to be around
,Nursing Connections
l
How is Regression Analysis used in Nursing? An Example
How is Regression Analysis used in Nursing? An Example
Regression analysis can be used in a variety of settings in health
care. Predicting future health concerns of a patient, future
staffing needs or future budgets are just some of the topics that
may be reviewed. Regression analysis uses multiple variables
that are known to be associated to predict future needs/concerns.
Is there a nursing shortage? Regression analysis is used to
evaluate supply and demand data for the health care industry and
nursing occupations to identify existing and potential nursing
workforce shortages and/or surpluses. Variables such as the
, number of currently licensed nurses, overall population growth,
the number of nursing planning to retire in the next 10 years,
and enrollment in nursing education programs are examined to
predict future workforce needs within the nursing profession.
Regression analysis*
When analyzing the relationship between two or more variables,
regression analysis is a helpful tool. Regression analysis* is used
when multiple variables' quantities relate to each other.
Regression analysis is an extension of scatterplots, associations,
and correlations. If we determine that an association exists
between two or more variables, we can use regression analysis
for description and prediction. Regression is used to describe a
trend or predict values based on known values.
Example of Regression Analysis
For example, a patient's weight is associated with blood
pressure, cholesterol, and blood sugar. These variables can be
modeled with a regression analysis. Once their association has
been established and quantified, regression analysis can be used
to predict future data values. So, we can quantify all of the
health risks a patient may have based on a risk factor: weight.
Recall that the response variable* is the
variable whose value "responds" to the other variables in the
equation; in the previous example, the response variable could
be blood pressure, cholesterol, or blood sugar, factors that are
Solutions
5. Which of the following best describes the correlation in the
scatterplot below?
Strong positive correlation
Strong negative correlation
Weak positive correlation
Weak negative correlation
swer is b. This scatterplot reveals a strong negative correlation.
A result is significant if it was likely caused by chance.
,True
False
ect
×
The answer is b. This statement is false. A result is significant if
it was unlikely to have been caused by chance.
A hypothesis test* A hypothesis test* will tell us whether the
results are statistically significant or not.
Estimate the correlation coefficient for the scatterplot in
question #5.
−0.92
−0.1
0.5
0.92
orrect
×
The answer is a. Weak correlations have correlation coefficients
close to 0. Because this is a strong negative correlation, the
correlation coefficient is negative and close to −1, so it can be
estimated to be around
,Nursing Connections
l
How is Regression Analysis used in Nursing? An Example
How is Regression Analysis used in Nursing? An Example
Regression analysis can be used in a variety of settings in health
care. Predicting future health concerns of a patient, future
staffing needs or future budgets are just some of the topics that
may be reviewed. Regression analysis uses multiple variables
that are known to be associated to predict future needs/concerns.
Is there a nursing shortage? Regression analysis is used to
evaluate supply and demand data for the health care industry and
nursing occupations to identify existing and potential nursing
workforce shortages and/or surpluses. Variables such as the
, number of currently licensed nurses, overall population growth,
the number of nursing planning to retire in the next 10 years,
and enrollment in nursing education programs are examined to
predict future workforce needs within the nursing profession.
Regression analysis*
When analyzing the relationship between two or more variables,
regression analysis is a helpful tool. Regression analysis* is used
when multiple variables' quantities relate to each other.
Regression analysis is an extension of scatterplots, associations,
and correlations. If we determine that an association exists
between two or more variables, we can use regression analysis
for description and prediction. Regression is used to describe a
trend or predict values based on known values.
Example of Regression Analysis
For example, a patient's weight is associated with blood
pressure, cholesterol, and blood sugar. These variables can be
modeled with a regression analysis. Once their association has
been established and quantified, regression analysis can be used
to predict future data values. So, we can quantify all of the
health risks a patient may have based on a risk factor: weight.
Recall that the response variable* is the
variable whose value "responds" to the other variables in the
equation; in the previous example, the response variable could
be blood pressure, cholesterol, or blood sugar, factors that are
