Saint Petersburg College Module 5 Health & Human Services Discussion Paper Module 5 Discussion Do you know the Difference? Students new to research often

Saint Petersburg College Module 5 Health & Human Services Discussion Paper Module 5 Discussion

Do you know the Difference?

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Saint Petersburg College Module 5 Health & Human Services Discussion Paper Module 5 Discussion Do you know the Difference? Students new to research often
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Students new to research often find some of the terms and concepts confusing as some of the terms may be used interchangeably in different areas of research, such as data and statistics. However, when reviewing scholarly research, it is important to understand the differences between some key terms.

For this discussion, I want you to take on the role of the instructor and explain the difference between the following terms: data, statistics, descriptive statistic, inferential statistic, statistical methods, and describe/identify an example of each that you find in a single research article from the SPC article databases

Post a working link and/or URL to your article (do not forget citations and references). Check out this Permalinks Tutorial to help you find a “Permalink” or “Persistent link” for your article so that you can post a direct link to the article. I recommend that you keep the tutorial for future reference (note, these links are what you should use for retrieval information in your APA formatted Reference entry when there is not a doi present).

You may wish go back and visit one of the early topics in the book, Empirical Research, as well as this week’s required reading. Outside reading is also recommended. I want to “hear” that you have a good understanding of these terms and the differences between them as you prepare to complete the next part of your Article Analysis

Module 6 Discussion

Applying Research Findings

You have been analyzing research studies for the past 6 weeks. Using the research article that you chose to analyze in Analysis 1 and Analysis 2, please address each of the following questions in your POSTING:

Effects of large financial incentives for long-term smoking cessation. A Randomized Trial, by Jean-François Etter and Felicia Schmid. This article is published in the Journal of the American College of Cardiology, Volume 68, Number 8, 2016.doi:

What experiment was taking place in your study
What did your research study mean to YOU?
What do you think the “take home message” is?
Will what you learned from this study alter YOUR practice behaviors?
Has this study influenced your professional THOUGHT? How?
Identify and RESPOND to one of your colleague’s postings
In that post, tell us something you learned from your colleague’s posting.
How might you APPLY this information to YOUR professional setting?

Module 7 Discussion

Protection of Human Subjects

As an overview for this forum, start by reading the content page titled : Unethical Research at Home, four specific atrocities are introduced briefly.

Please search the Internet to find an electronic report on ONE of these research atrocities/human experimentation examples listed below.

Tuskegee Terre Haute Prison Experiment
Willowbrook Belleview Electro Shock Experiments
Jewish Chronic Disease Hospital Study Eugenics laws for forced sterilizations
Human Radiation Experiment The Milgram Experiment
Stanford Prison Experiment Little Albert Study
The Monster Study Emma Eckstein Study
Pellagra Incident The Monkey Drug Trials
1940 Chicago Malaria Study The Bobo Doll Experiment
Chemical Warfare Services studies completed by the U.S. Army (many – find a specific one)

The Landis Facial Expressions Experiment

CIA studies related to mind control and LSD (find a specific one as there are several, i.e., Project MK-ULTRA) Harry Harlow – The Pit of Despair Experiment
U.S. Army germ/biological warfare studies (find a specific one, there are many!) John Darley and Bibb Latane – The Bystander Effect
U.S. Army Mustard gas and lewisite experiments Racism among Elementary School Students – Jane Elliott
U.S. Military Yellow Fever studies UCLA Schizophrenia Experiments
Pennsylvania Prison studies related to Dioxin Loftus Lost in the Mall Study
SV40 Virus contamination of the Polio Vaccine Dr. William Beaumont – The Hole in the Stomach study
Guatemala Syphilis Experiment

For this forum:

Provide a working link and/or URL to your electronic report OR attach a copy of your report to the Discussion forum.
Provide the title of the Experiment or Research
Provide the date(s) of when it took place
In a 250-300 word post please share with all of us: Give an overview of the content of your report – in your own words (Do not cut and paste – you will not receive points if you do).
Describe your reaction to what you read.
Name and describe ( using the section number or titles) 1 specific standard that is now in place through the IRB: Title 45 Protection of Human Subjects that may help protect subjects from the uneithical action that you discovered in your readings. Select one from the Guidebook OR the Health and Human Services link: Title 45 Protection of Human Subjects. For example, in the HHS link I might NAME: 46.116 General Regulations for Informed consent and then DESCRIBE, in my own words the specifics of this section. Descriptive Statistics
A statistic is a numeric characteristic of a sample
A parameter is a numeric characteristic of a population
Descriptive Statistics are used to:
organize, condense and summarize data with numbers and pictures
pictures: frequency distributions and graphs (histogram, polygon)
o measures of central tendency: mean, median, mode
o measures of variation: range, standard deviation
Measures to Condense Data
Frequency Tables
DATA SET: ages of 12 randomly selected members of our HSA 3702 Research Class
(sample size is n=12)
Measures of Central Tendency
mean: arithmetic average; add all ages divide by “n.”
median: arrange data set in ascending or descending order and select the middle
value. If there is an even # in the data set
calculate a mean of the middle two numbers.
mode: variable that occurs the most.
Now you try: use our data set above to calculate
Mean age of our research class_______________
Median age of our research class_____________
Mode of our research class____________________
How did you do?
mean of our data set: 35.6 years
median of our data set: 33.5
mode of our data set 25
These are ALL measures of central tendency aka “averages” and look how much they
Does your assignment research article use an “average?”
Do the authors alert the reader to which “average” they used: mean? median? mode?
Measures of variability
range: difference between highest and lowest value in your collected data.
According to our data set, what is the range of ages in our class? _______
Answer: 41 years
Standard deviation of a data set is the average deviation of each of our ages from the
mean. Just remember the concept. We will be using it later on in the module.
Inferential Statistics
Inferential statistics, are those statistics that use sample data to make decisions or
‘inferences’ about a population. Populations are the groups of interest when inferential
statistics are used even though the data are analyzed from samples.
There are two broad purposes of inferential statistics:
estimating population parameters using sample data
testing hypotheses
Population parameters
To estimate population parameters from sample data, an understanding of sampling
error and sampling distribution are necessary.
Sampling errors occur when a sample does NOT accurately reflect the population.
Whenever we use a sample to make inferences about a “population”… matter how
careful we are to select a representative sample….there is a chance for sampling error.
For example, suppose 25 of our BASHSA students were randomly selected to represent
all of our BAS students at SPC on a standardized test administered by the college. The
sample’s mean score on the test was 70 and the standard deviation was 10.
Would we have obtained the exact same mean score on the standardized test if we had
used every person in the BAS programs at SPC in our calculation of the mean and
standard deviation? Most likely, not. As Patten (2014) indicates: random sampling
produces random errors. At first, this situation might seem rather hopeless but,
fortunately, the effects of random sampling errors are fairly predictable.
Here is how:
A widely reported inferential statistic is the margin of error. It is a type of standard
deviation. The margin of error expresses the amount of random sampling error in a
research study’s results. This statistic helps us, the readers of the research study, to
interpret the study’s results in light of sampling error. To calculate this inferential statistic
we need to divide the standard deviation by the square root of the sample size. We
have all the data we need.
Our standard deviation is 10 and our sample size is 25. Now plug it into the formula:
The square root of 25 is 5 so the square root of our sample size is 5.
When we divide our standard deviation of 10 by 5 we have a margin of error of 2.
Margin of Error = 2
Sampling distribution
Now that we know that the margin of error we are able to make some interesting
predictions with varying degrees of confidence.
In order to make these predictions we need to think back on the concept of the central
limit theorem that perhaps you might remember from earlier science classes? It states
that a sampling distribution of means forms a normal curve. The readings in Topic 53
and Appendix D reiterate this concept.
When there are a number of sample values that are arranged in a frequency
distribution, those values will be normally distributed.
IN FACT, 68% of those values will fall within 1 standard deviation above and below the
mean; 95% of those values will fall within 2 standard deviations above and below the
mean and 99% will fall within 3 standard deviations above and below the mean!
With these facts in mind, consider a practical use of the margin of error: Confidence
Confidence intervals
Specifically, the margin of error can be used to build 68%, 95% and 99% confidence
intervals (CI) for constructing a population mean from a sample mean.
A confidence interval (CI) is a range of values that, with a specified degree of
probability, is thought to contain the population value.
In everyday terms we could say that while we found that the mean standardized test
score of our sample was 70, the value might have been influenced by sampling errors.
To account for these errors a more reliable estimate of the true population mean is that
the mean score would fall between 68 and 72. We could report this interval with 68%
How did we come up with this interval? By adding and subtracting the Margin of Error
(2) from our sample mean.
It is much more common for researchers to report 95% and 99% confidence intervals
instead of the 68%.
Using our concept of the normal curve, we would subtract & add 2 margin of error units
(4) for a 95% Confidence Interval AND 3 margin of error units (6) for a 99% Confidence
OK, now you give it a try:
Using a random sample of BASHSA students with a standardized test score of 70 and a
margin of error of 2, we could be 95% confident that the mean test score of all BAS
students at SPC lies between ____________and ______________. We could have
99% confidence that the mean test score of ALL BAS students at SPC lies between
How did you do?
We could have 95% confidence that the mean test score of all BAS students lies
between 66 and 74.
We could have 99% confidence that the mean test score of all BAS students lies
between 64 and 76.
Levels of measurement
Before determining the appropriate data analysis procedures that will be used to test a
hypothesis, a researcher must understand the level of measurement being collected by
the study’s data collection tool aka measurement instrument.
The level of measurement dictates which statistical procedures can be used. For
example, if a researcher has collected nominal level data, a mean cannot be calculated
on the data.
There are four levels of measurement.
Nominal level
categories: Republicans, Democrats, males, females, yes, no
no rank order. You cannot say that Republicans are higher on a scale than
counting is the only mathematical operation you can do with nominal level data:
10 Republicans/4 Democrats; 16 yes/11 no.
mode is the only measure of central tendency that can be done on nominal data
Ordinal level
numbers specify the orde,r but there is no certainty that the intervals between
ranked categories are equal
example: a rubric might have a rank-order of 0-6 for content. Each of the
numbers stand for specific criteria. Where 5 is excellent, several sentences follow
to describe what “excellent” means. Only as a result of the sentence descriptions
do we know that excellent is better than good.
a researcher is able to rank-order the respondents or their responses to
questions because one category is ranked higher or lower, better or worse than
many health care scales use ordinal level data
median and mode are measures of central tendency with ordinal data
Reports of nominal data might state: most (mode) of the students in the research
class scored “good” or better on their article analysis content.
Or, the median content score was “good.”
Interval level
intervals between the numbers are meaningful and can be compared, but there is
no absolute zero
example: the average temperature in St. Petersburg was 60 degrees
Fahrenheit in January 2013 and could be meaningfully compared to the average
temperature of 55 degrees in January 2012.
mean, median and mode can be calculated using interval data.
Ratio level
possesses a true zero
a 20 pound turkey is twice as heavy as a 10 pound turkey
weight measurement, length, cell counts, oxygen saturation
mean, median, mode can be calculated using ratio level data
Think about this…..
If you think back to your problem statement in Module 1 and the data that you would
need to collect in order to answer your research problem statement, what level of
measurement would you use?
Would you be able to calculate a mean? median? mode?
Ethical Considerations
1932, US Public Health Service initiated a study of syphilis in African-American
Study continued for 40 years, finally discovered and stopped in 1972
Purpose was to study the natural course of disease in African-American men
Lacked informed consent
Withheld available treatment from subjects
Tuskegee apology, human experimentation
Willowbrook Study (New York)
Mid 1950 s to early 1970 s research was conducted by Dr. Saul Krugman at the
Willowbrook Institution for the Mentally Retarded
Mentally retarded children deliberately injected with hepatitis
Parents were forced to give consent for their children to be in the study in order
to obtain placement at the facility. Willowbrook was overcrowded and only the
research wing would admit new patients.
Persons conducting the study defended it by saying that the children would have
gotten hepatitis anyway by being exposed to everyday conditions at a mental
institution and that because of the study funding the children benefited from a
clean environment, better supervision and higher nurse patient ratio
Jewish Chronic Disease Hospital Study (New York)
Occurred in 1960’ s
Patients injected with cancer cells to determine the body’s ability to reject cancer
Patients were not informed regarding research or injection of live cancer cells
Physicians caring for patients were unaware of research
Human Radiation Experiments
On April 10, 1945, medical staff of the U.S. Manhattan Engineer District in Oak
Ridge, TN, injected plutonium into the victim of a car accident
American scientists had only recently begun producing plutonium and thousands
of workers were laboring to produce the quantities required for the first atomic
While aware that plutonium was hazardous, project officials were uncertain how
much exposure would cause harm.
Desire for information about human metabolism and retention of plutonium led to
this first injection in Oak Ridge.
Over the next 2 years, 17 other people also received plutonium injections.

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