When you are working on the Inferential Statistics Paper I want you to format your paper with the following information I.                    Introduction – What are inferential statistics and what is the research problem and hypothesis of the article? II.                  Methods – Who are the subjects and variables within the article? III.                Results – What is the statistical analysis used, why were these tests chosen? What were the results of these tests and what do they mean? IV.                Discussion – What were the strengths of this article? What would you have done differently in terms of variables and statistical analysis? Why? V.                  Conclusion – Reiterate the introduction and include relevant information that answers the questions regarding the hypothesis. ` Read:  Chapter 3 and 4 of Statistics for the Behavioral and Social Sciences.          Participate in One discussion.          Discussion 1 –Standard Normal Distribution– This allows you to look at any data set into the standard distribution form.          Quiz – Hypothesis testing          Submit your Inferential Statics Article Critique – Read Differential Effects of a Body Image Exposure Session on Smoking Urge Between Physically Active and Sedentary Female Smokers.  What is the research question and hypothesis? Identify what variables were present, what inferential statistics were used and why, and if proper research methods were used. See grading rubric for full details. Discussion Post Expectations: Your initial post (your answer) is due by Day 3 (Thursday) of this week for Discussion 1. When grading the Standard Normative Distribution discussion I will be looking for your answer to contain: Week 2 Discussion 1 Board Rubric      Earned Weight Content Criteria 0.5 Student identifies and defines what Standard Normative Distribution (SND) is. Student explains why it is needed to use a SND to compare two data sets. 0.5 Student identifies the purpose of a z-score in a SND. 0.5 Student identifies the purpose of a percentage in a SND. 0.25 Student explains whether a z-score or a percentage does a better job of identifying proportion of a SND. 0.25 The student responds to at least two classmates’ initial posts by Day 7. 1 Student uses correct spelling, grammar and sentence structure. 2 5 Grading - The discussions are both worth a total of 5 points. The breakdown of the grading for this week’s assignment (per discussion assignment) will be as follows:          Posting your answer by the due date (Day 3, Thursday) is worth 4 points. These five points will be based on the information outlined within the Discussion Assignment Expectations. Content will be worth 2 points and format; spelling and grammar will be worth 2 points.          Responding to two of your classmates (for each assignment) is worth 1 point. The answers must be substantive and go beyond “I agree” or “Good job” to qualify for this point. Intellectual Elaboration: In Wee.

1. When you are working on the Inferential Statistics Paper I want
you to format your paper with the following information
I. Introduction – What are inferential statistics and
what is the research problem and hypothesis of the article?
II. Methods – Who are the subjects and variables
within the article?
III. Results – What is the statistical analysis used,
why were these tests chosen? What were the results of these
tests and what do they mean?
IV. Discussion – What were the strengths of this
article? What would you have done differently in terms of
variables and statistical analysis? Why?
V. Conclusion – Reiterate the introduction and
include relevant information that answers the questions
regarding the hypothesis.
`
Read: Chapter 3 and 4 of Statistics for the Behavioral and
Social Sciences.
Participate in One discussion.
Discussion 1 –Standard Normal Distribution– This
allows you to look at any data set into the standard distribution
form.
Quiz – Hypothesis testing
Submit your Inferential Statics Article Critique –
Read Differential Effects of a Body Image Exposure Session on
Smoking Urge Between Physically Active and Sedentary Female
Smokers. What is the research question and hypothesis?
Identify what variables were present, what inferential statistics
were used and why, and if proper research methods were used.
See grading rubric for full details.
Discussion Post Expectations:
Your initial post (your answer) is due by Day 3 (Thursday) of
this week for Discussion 1.

2. When grading the Standard Normative Distribution discussion I
will be looking for your answer to contain:
Week 2 Discussion 1 Board Rubric
Earned
Weight
Content Criteria
0.5
Student identifies and defines what Standard Normative
Distribution (SND) is.
Student explains why it is needed to use a SND to compare two
data sets.
0.5
Student identifies the purpose of a z-score in a SND.
0.5
Student identifies the purpose of a percentage in a SND.
0.25
Student explains whether a z-score or a percentage does a better
job of identifying proportion of a SND.
0.25
The student responds to at least two classmates’ initial posts by
Day 7.
1
Student uses correct spelling, grammar and sentence structure.
2

3. 5
Grading - The discussions are both worth a total of 5 points.
The breakdown of the grading for this week’s assignment (per
discussion assignment) will be as follows:
Posting your answer by the due date (Day 3, Thursday)
is worth 4 points. These five points will be based on the
information outlined within the Discussion Assignment
Expectations. Content will be worth 2 points and format;
spelling and grammar will be worth 2 points.
Responding to two of your classmates (for each
assignment) is worth 1 point. The answers must be substantive
and go beyond “I agree” or “Good job” to qualify for this point.
Intellectual Elaboration:
In Week 1 we looked at descriptive statistics and how we can
use numbers and charts to explain how data looks and what it
means. This week we will look at inferential statistics which
means we are looking at what the data means, or could mean, in
practical application to a population (if we can prove or
disprove a hypothesis) (Tanner, 2011).
The z-test outlined in chapter 4 tells how we apply the z-score
to the z-test. One of the limitations of the z-test is that it does
not allow us to compare two variables within two samples it
only allows us to look at a sample group and applying it to a
whole population. In Week 1’s guidance we looked at a group
of students test scores in a class. With a z-test we can look at
this sample and apply the results to all students who take the
same course and make a prediction about how all students
within the course will do on the same test. What we could not
do would be to look at the results of the test scores after
preforming the z-test and compare it to the GPA’s of students
within the class to see if students who received lower scores on
the test also had lower GPA’s. Also without access to the mean
of the population and the standard error of mean of the
population all of the student’s GPA’s could not be determined,
thus access to the data could also be a large hurdle to overcome

4. to make this correlation (Tanner, 2011).
Looking at the t-test, unlike a z-test which looks at a sample
and applies it to a population the t-test allows us to look at the
means of the two different groups being studied to see if they
are statistically different from each other. The way this is most
commonly used is within research to see if the independent
variable had an effect on the population being studied and if a
change in the population was made (ChangingMinds.org,
2012). How does a t-test determine if the independent variable
applied to a population caused change? To do this researchers
look at whether the null hypothesis is true, meaning that no
change occurred. Researchers will look to see if the mean of the
experimental sample is the same as the mean of the sample the
experimental population is being compared to is the same. If it
is then no change has occurred and the null hypothesis is true
(Tanner, 2011).
So let’s say we have gathered the data and ran the t-test, how do
we know what the results mean? Are the results significant
(meaning that our alternative hypothesis is proved to be
true)? In order to do this we need 4 things.
1. The number of subjects we have. (df which is n – 1 or your
total number of subjects -1)
2. To know if you have a one tailed or two tailed t-test (which
we will look at more closely in Week 3).
3. The probability that you have chosen (typically .05).
4. T distribution critical values table (Gerstman, 2007). You can
see this table below under the Additional Resources section.
When you use the df and look at the probability for the one or
two tailed t-test you will see the what result you need from your
t-test to see if your results are statistically significant. For
example of you had a df of 15 (which means you had 16
subjects) and a p< 0.05 and a one tailed t-test you need a result
at or above 1.753 in order for the results to be statistically
significant, meaning there is a difference between the two
variables you are testing and you would reject the null
hypothesis and accept the alternative hypothesis.

5. For example if researchers were testing an HIV drug and wanted
to see of Drug X had an effect of raising the white blood cell
count they would test the group that received the independent
variable (Drug X) against a control group that did not receive
the drug. If after running the t-test they found that the group
that received Drug X had a mean that was the same as the
control group for the number of white blood cell’s present then
there would be no change and they would accept the null
hypothesis. In the event that the means of the population who
received Drug X is different than the population that did not
this would not mean that the drug works, it would mean they
failed to reject the null hypothesis (Tanner, 2011) and that
further study is needed to determine if Drug X has a therapeutic
effect.
Charts from Week 1 provide visual representations of
data. What happens if we chart the data and it is hard to
understand? This is where the standard normal distribution
comes into play. By applying this we can place data is the bell
curve you are familiar with seeing. The tallest part of the bell
curve will be the median of the scores. In this deviation all the
data will be towards the center with no bias towards the right or
the left when graphed out. Some key factors about a standard
normal distribution that may not be present in other forms of
data is that there is a mean, median and mode which will be
within the center of the data, approximately 50% of the data
will be above the mean and 50% of the data will be below the
mean, 68% of all the data will be within 1 standard deviation of
the mean (1 deviation above and below the mean), 95% of the
data will be within 2 standard deviations of the mean (2
deviations above and below the mean), and 99.7% of the data
will be within 3 standard deviations of the mean (3 deviations
above and below the mean (MathisFun, 2012).
(Pullen, 2010).
So knowing this, the question is why standardize your data, why
not just graph it out and let it fall where it will? The simplest
answer it is that will make your job easier as you will only need

6. one table and it will provide more accurate data to assist you
with making your decision. If you look at the example of the
grades there are several different tables to look at the grades to
get the information you need. What if you are teaching a class
and you have 40 assignments and you were trying to find the
same information? You would need to alter the data to get an
idea of how many students fell in the A,B, C, D, and E range, a
different graph to see if there was a skew in the data, if there is
kurtosis etc. This type of graphing of data will also allow you to
see probability, what is the likely-hood that a student will fall
into each grade range (Tanner, 2011)?
Consider the following sample of students who took a test: 85,
90, 96, 77, 63, 86, 88, 72, 74, 98, 100, 85, 83, 72, 62, 87, 92,
93, 84, 86, 75, 82, 78, 73, 64, 74, 92, 87, 39, 55, 94, 79, 73, 88,
83, 84, 75, 67, 74, 86, 85, 67
You could do several calculations and find out the mean,
median, mode and then determine how the class was doing by
creating several different graphs using several different
calculations. Or you can use the standard normal distribution to
analyze all the data at once.
Tests
Mean
79.69048
Standard Error
1.882584
Median
83
Mode
85
Standard Deviation
12.20054
Sample Variance
148.8531
Kurtosis

7. 1.767116
Skewness
-0.99429
Range
61
Minimum
39
Maximum
100
Sum
3347
Count
42
What the analysis tells us is that the Mean Score (0 of the
Standard Normative Deviation) is 79.69 and the standard
deviation is 12.20 points. So 68% of the data will fall between
67.49 (which is -1 of the standard deviation) and 91.89 (which
is +1 of the standard deviation). The skew of this data set is -
.99 which means that there is a slight negative skew (more
students fell above the mean than below the mean and that the
median score is higher than the mean score). Looking at the
kurtosis of this data is 1.77. Looking we see that the standard
deviation (s) is greater than R( ) where R=Range of 61 divided
by 6 so s>R/6 looks like 12.20>61/6 or 12.20>10.67. This
means that the kirtosis of this data set is platykurtic, meaning
that the data within the set is too varied to be a normal curve
and it is flatter as in figure 2.6 of your text (Tanner, 2011).
Additional Resources (web links, videos, and articles):
Independent Samples T-Test
http://www.youtube.com/watch?v=Ojo-n-riYj8
Statistics – Standard Normal Deviation
http://www.youtube.com/user/EducatorVids2?v=drk8yzFoWSE
&feature=pyv
T Distribution Critical Values Table
http://www.sjsu.edu/faculty/gerstman/StatPrimer/t-table.pdf

8. Please watch video: Probability Distributions
References:
Gerstman, B. (2007). T Distrabution and Critcal Values Table.
Retrieved
from http://www.sjsu.edu/faculty/gerstman/StatPrimer/t-
table.pdf
MathisFun (2012). Normal Distribution. Retrieved
from http://www.mathsisfun.com/data/standard-normal-
distribution.html
Pullen, P.C. (2010). Understanding Standard Scores. Retrieved
from http://www.faculty.virginia.edu/PullenLab/WJIIIDRBMod
ule/WJIIIDRBModule7.html
Tanner, D. (2011). Statistics for the behavioral & social
sciences. San Diego, CA: Bridgepoint Education, Inc.
Standard Normal Distribution
For this discussion, identify the appropriate application of
standardized scores to reflect on their benefits and to interpret
how test scores and measures are commonly presented.
Review Chapter 3 of your course text, which introduces
probability and the standard normal distribution. Examine the
assumptions and limitations presented in these topics and then
consider and discuss the following questions:
· When comparing data from different distributions, what is the
benefit of transforming data from these distributions to
conform to the standard distribution?
· What role do z-scores play in this transformation of data from
multiple distributions to the standard normal distribution?
· What is the relationship between z-scores and percentages?
· In your opinion, does one do a better job of representing the
proportion of the area under the standard curve? Give

9. an example that illustrates your answer.
Guided Response: Review your classmates’ posts. Respond
substantively to at least three peers. What did you find useful
about their explanations and examples? What suggestions
would you make for improvement? Ask a question for further
clarification as to the meaning and use of the z-scores.
Inferential Statistics Article Critique
Read the article "Differential Effects of a Body Image Exposure
Session on Smoking Urge Between Physically Active and
Sedentary Female Smokers," and identify the research questions
and/or hypotheses as they are stated. Consider the following
questions: What are the variables (sample sizes, population,
treatments, etc.)? What are the inferential statistics used in this
article? Were the proper steps of hypothesis testing followed?
Write a two- to three-page paper presenting the information
listed below. Include a title page and reference page in APA
style. Cite any references made to the article within the body of
the paper in APA style. Your paper should begin with an
introductory paragraph (including a thesis statement) and end
with a concluding paragraph summarizing the major points
made in the body of the paper and reaffirming the thesis. When
writing the article critique, your paper must:
1. Determine what question(s) the authors are trying to answer
by doing this research.
2. Determine the hypothesis being tested and the concepts that
were applied in this process.
3. Evaluate the article and critique the statistical analysis
employed in the study.
· Would you have included more and/or different variables?
Explain your answer.
4. Examine the assumptions and limitations of the statistical
study.

10. · What would you have done differently in this case? Why?
5. Identify how the authors applied statistical testing to the
problem.
6. Interpret the findings of the author(s) using statistical
concepts.
You may access the Critical Thinking Community website for
tips on how to formulate your thoughts and discussion of these
questions in a logical and meaningful manner.
Writing the Article CritiqueThe Assignment:
1. Must be two to three double-spaced pages in length
(excluding title and reference pages), and formatted according
to APA style as outlined in the Ashford Writing Center.
2. Must include a title page with the following:
a. Title of paper
b. Student’s name
c. Course name and number
d. Instructor’s name
e. Date submitted
3. Must document all sources in APA style, as outlined in the
Ashford Writing Center.
4. Must include a separate reference page, formatted according
to APA style as outlined in the Ashford Writing Center.