HLT 362V Module 2 Population Sampling Distribution

HLT 362V Module 2 Population Sampling Distribution

HLT362V

For a normal distribution that has a mean of 100 and a standard deviation of 8. Determine the Z-score for each of the following X values:

X = 108

X = 112

X = 98

X = 70

X = 124

Use the information in 1 A to determine the area or probability of the following:

P(x > 108)

P(x

HLT 362V Module 1 Mean Variance Standard Deviation

Please type you answer in the cell beside the question.

1. Identify the sampling technique being used. Every 20th patient that comes into the emergency room is given a satisfaction survey upon their discharge.
2. random sampling
3. cluster sampling
4. systematic sampling
5. stratified sampling
6. none of the above
7. The formula for finding the sample mean is ______________.
8. The formula for finding sample standard deviation is ________________.

HLT 362V Module 1 Exercise 16 Done

1- The researchers analyzed the data they collected as though it were at what level of measurement? (Your choices are: Nominal, Ordinal, Interval/ratio, or Experimental)

2- What was the mean posttest empowerment score for the control group?

3- Compare the mean baseline and posttest depression scores of the experimental group. Was this an expected finding? Provide a rationale for your answer.

4- Compare the mean baseline and posttest depression scores of the control group. Do these scores strengthen or weaken the validity of the research results? Provide a rationale for your answer.

5- Which group’s test scores had the least amount of variability or dispersion? Provide a rationale for your answer.

6 – Did the empowerment variable or self-care self-efficacy variable demonstrate the greatest amount of dispersion? Provide a rationale for your answer.

7 – The mean (X ̅) is a measure of a distribution while the SD is a measure of its scores. Both X ̅ and SD are statistics.

8 – What was the mean severity for renal disease for the research subjects? What was the dispersion or variability of the renal disease severity scores? Did the severity scores vary significantly between the control and the experimental groups? Is this important? Provide a rationale for your answer.

9 – Which variable was least affected by the empowerment program? Provide a rationale for your answer.

10 – Was it important for the researchers to include the total means and SDs for the study variables in Table 2 to promote the readers’ understanding of the study results? Provide a rationale for your answer.

 

 

MORE INFO 

Population Sampling Distribution

Introduction

The population of a country is the total number of people in that country.

In this section we will learn about sampling distributions and how to estimate them. We will also discuss how statistics are used to estimate parameters from samples.

Population

Population is a group of individuals or items.

It can be finite or infinite, depending on how many people there are in it.

Sample

The sample is a subset of the population. Sampling is used to draw samples from populations and then estimate some characteristic or parameter in those samples.

The sampling distribution is a theoretical distribution of the statistic being sampled (e.g., mean, median) when we repeatedly draw samples from the population. The sampling distribution can be used to determine how precise we are willing to be in estimating our estimation statistic given a certain error level or other constraint on what we want to estimate.

Sampling distribution

The sampling distribution of a sample mean is called the sampling distribution of N(μ, σ).

The mean of a random sample from a normal distribution with unknown variance (σ) is called the population mean. It is denoted by μ and has been estimated to be equal to 68.3. The standard deviation (σ) measures how spread out or “spread out” your data are around their mean value; it’s easy to see why this matters if you’re graphing something!

Population parameter

The population parameter is the mean of the entire population. It’s not just what you think it is. It’s not your average, but rather a true value that describes how your data collection looks like in total as opposed to being an average over individuals or samples.

The population parameter can also be used as a measure of central tendency (a common sense definition). For example, if you wanted to find out what percentage of people had blue eyes among all humans on earth, then we could first calculate their mean eye color and divide by their number (N) so we know how many people have blue eyes out there! This would give us our true estimate for this characteristic within our entire species—that is: 1%~2%~4%.

Statistics

Statistics is a branch of mathematics that deals with the collection, analysis, interpretation and presentation of data. It is used to summarize and describe data as well as make predictions about future events using statistical models. Statistics also provides a framework for making decisions based upon probability theory or sampling distributions.

Statistics can be used to study relationships between variables in order to predict outcomes based on past observations (hypothesis testing). For example: if you have collected 100 samples of size n from a population with unknown mean μ and standard deviation σ then you will have collected 100(n-1) pairs of values x = [μx + μy]/2 where y = [0; 1]. This means that within each sample there were two possible outcomes for y; either 0 or 1 (or possibly 2). If we know the probability distribution function p(y) then we can find out how likely it is that y will take one particular value from the set 0 through 9 by plugging into your formula like so: P(y=0)=1/2 so there’s only one way this could happen – 0! Similarly P(y=1)=9/100 so there are nine ways in which this could happen – 9 ones!

Takeaway:

• The sampling distribution is the distribution of sample statistics.

• It’s often bell shaped, and it has a mean (population parameter) and standard deviation (standard error). We will look at this for the binomial distribution.

Conclusion

This is a great way to practice your statistics with the distribution function. Keep working on it until you can get all the answers!