MATH 225 EXAM
PREP VERIFIED
Statistical Reasoning for the
Health Sciences
2023
, 1. What is the difference between descriptive and inferential statistics? Give an example of
each in the context of nursing research.
- Descriptive statistics summarize and display the characteristics of a data set, such as mean,
median, mode, standard deviation, frequency, etc. Inferential statistics use sample data to
make generalizations or predictions about a population or a hypothesis, such as t-test,
ANOVA, regression, etc. For example, descriptive statistics can be used to report the average
age, weight, and blood pressure of a group of patients, while inferential statistics can be used
to test whether there is a significant difference in the blood pressure between two groups of
patients who received different treatments.
2. What is the difference between a parameter and a statistic? Give an example of each in the
context of nursing research.
- A parameter is a numerical value that describes a characteristic of a population, such as the
mean, proportion, or standard deviation. A statistic is a numerical value that describes a
characteristic of a sample, such as the sample mean, sample proportion, or sample standard
deviation. For example, the parameter of interest could be the proportion of smokers among
all adults in the US, while the statistic of interest could be the proportion of smokers among a
sample of 100 adults from a hospital.
3. What is the difference between a null hypothesis and an alternative hypothesis? Give an
example of each in the context of nursing research.
- A null hypothesis is a statement that assumes no difference or no effect between two or
more groups or variables. An alternative hypothesis is a statement that contradicts the null
hypothesis and assumes some difference or some effect between two or more groups or
variables. For example, the null hypothesis could be that there is no difference in the pain
level between patients who received acupuncture and patients who received placebo, while
the alternative hypothesis could be that there is a difference in the pain level between patients
who received acupuncture and patients who received placebo.
4. What is the difference between a type I error and a type II error? Give an example of each
in the context of nursing research.
- A type I error is when we reject the null hypothesis when it is true. A type II error is when
we fail to reject the null hypothesis when it is false. For example, a type I error could be when
we conclude that there is a significant difference in the pain level between patients who
received acupuncture and patients who received placebo, when in fact there is no difference.
A type II error could be when we conclude that there is no significant difference in the pain
level between patients who received acupuncture and patients who received placebo, when in
PREP VERIFIED
Statistical Reasoning for the
Health Sciences
2023
, 1. What is the difference between descriptive and inferential statistics? Give an example of
each in the context of nursing research.
- Descriptive statistics summarize and display the characteristics of a data set, such as mean,
median, mode, standard deviation, frequency, etc. Inferential statistics use sample data to
make generalizations or predictions about a population or a hypothesis, such as t-test,
ANOVA, regression, etc. For example, descriptive statistics can be used to report the average
age, weight, and blood pressure of a group of patients, while inferential statistics can be used
to test whether there is a significant difference in the blood pressure between two groups of
patients who received different treatments.
2. What is the difference between a parameter and a statistic? Give an example of each in the
context of nursing research.
- A parameter is a numerical value that describes a characteristic of a population, such as the
mean, proportion, or standard deviation. A statistic is a numerical value that describes a
characteristic of a sample, such as the sample mean, sample proportion, or sample standard
deviation. For example, the parameter of interest could be the proportion of smokers among
all adults in the US, while the statistic of interest could be the proportion of smokers among a
sample of 100 adults from a hospital.
3. What is the difference between a null hypothesis and an alternative hypothesis? Give an
example of each in the context of nursing research.
- A null hypothesis is a statement that assumes no difference or no effect between two or
more groups or variables. An alternative hypothesis is a statement that contradicts the null
hypothesis and assumes some difference or some effect between two or more groups or
variables. For example, the null hypothesis could be that there is no difference in the pain
level between patients who received acupuncture and patients who received placebo, while
the alternative hypothesis could be that there is a difference in the pain level between patients
who received acupuncture and patients who received placebo.
4. What is the difference between a type I error and a type II error? Give an example of each
in the context of nursing research.
- A type I error is when we reject the null hypothesis when it is true. A type II error is when
we fail to reject the null hypothesis when it is false. For example, a type I error could be when
we conclude that there is a significant difference in the pain level between patients who
received acupuncture and patients who received placebo, when in fact there is no difference.
A type II error could be when we conclude that there is no significant difference in the pain
level between patients who received acupuncture and patients who received placebo, when in
