EPS 625 – INTERMEDIATE STATISTICS WILCOXON TEST
The Wilcoxon test was developed to analyze data from studies with repeated-measures and matched-subjects designs. For a repeated-measures design, an individual is assessed on a measure on two occasions or under two conditions. Each individual is a case in the SPSS data file and has scores on two variables, the score obtained on the measure on one occasion (or under one condition) and the score obtained on the measure on a second occasion (or under a second condition). The goal of repeated-measures designs is to determine whether participants changed significantly across occasions (or conditions). For a matched-subjects design, participants are paired, typically on one or more nuisance variables, and each participant in the pair is assessed once on a measure. Each pair of participants is a case in the SPSS data file and has scores on two variables, the score obtained on the measure by one participant under one condition and the score obtained on the measure by the other participant under the other condition. The purpose of matched-subjects designs is to evaluate whether the pairs of participants differ significantly under the two conditions. For both types of studies, each case in the SPSS data file has scores on two variables (that is, paired scores). The Wilcoxon test evaluates differences between paired scores, either repeated or matched. The variables for the Wilcoxon test have multiple possible scores, with the focus on whether the median of the variables differs significantly. The Wilcoxon test can be used to analyze data from a number of different designs: 1. 2. 3. 4. Repeated-measures designs with an intervention Repeated-measures designs without an intervention Matched-subjects designs with an intervention Matched-subjects designs without an intervention

UNDERSTANDING THE WILCOXON TEST
To help understand the Wilcoxon test, we will first describe what data are being analyzed. We will look at an example...

...1. He didn’t pass his driving test. He wishes he _____ it.
A) have passed B) had passed
C) will pass D) pass
2.I have to work about 80 hours a week, so I’m very busy. But if I_____ any spare time, I _____ a sport like golf.
A) will have / will take up
B) had / will take up
C) will have / had
D) had / would take up
4. He ______ in the library every night for the last two months.
A) would be studying
B) will have studied
C) has been studied
D) has been studying
5.A: Would you like me to give Mike a message for you?
B: Oh, I don’t want to trouble you.
A: It’s no trouble, really. I ______ Mike tomorrow anyway.
A) am seeing
B) saw
C) have seen
D) would see
6. You’re always late. This is the third time you ______ late this week.
A) had been B) were
C) have been D) will be
7. A: I’ve planned my future for the next five years.
B: That is very clever of you. What ______ when you retire?
A) will you do B) are you going to do
C) do you do C) have you done
8. I didn’t answer the phone when it ______ because I ______ a shower, so I ______ it until it was too late.
A) rang / was having / didn’t hear
B) rung / was having / wasn’t heard
C) was ringing / had / didn’t hear
D) rang / was having / wasn’t heard
9.No one brought up that question at the meeting. That question______ up at the meeting.
A) was brought
B) won’t be brought
C) hasn’t been brought
D) wasn’t brought
10.A: What do they use this building for?
B:...

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...Elements of a Test of Hypothesis 1. Null Hypothesis (H0 ) - A statement about the values of population parameters which we accept until proven false. 2. Alternative or Research Hypothesis (Ha )- A statement that contradicts the null hypothesis. It represents researcher’s claim about the population parameters. This will be accepted only when data provides suﬃcient evidence to establish its truth. 3. TestStatistic - A sample statistic (often a formula) that is used to decide whether to reject H0 . 4. Rejection Region- It consists of all values of the teststatistic for which H0 is rejected. This rejection region is selected in such a way that the probability of rejecting true H0 is equal to α (a small number usually 0.05). The value of α is referred to as the level of signiﬁcance of the test. 5. Assumptions - Statements about the population(s) being sampled. 6. Calculation of the teststatistic and conclusion- Reject H0 if the calculated value of the teststatistic falls in the rejection region. Otherwise, do not reject H0 . 7. P-value or signiﬁcance probability is deﬁned as proportion of samples that would be unfavourable to H0 (assuming H0 is true) if the observed sample is considered unfavourable to H0 . If the p-value is smaller than α, then reject H0 . Remark: 1. If you ﬁx α = 0.05 for your test, then...

...The T-Test
Page 1 of 4
Home » Analysis » Inferential Statistics »
The T-Test
The t-test assesses whether the means of two groups are statistically different from
each other. This analysis is appropriate whenever you want to compare the means of
two groups, and especially appropriate as the analysis for the posttest-only two-group
randomized experimental design.
Figure 1. Idealized distributions for treated and comparison group posttest values.
Figure 1 shows the distributions for the treated (blue) and control (green) groups in a
study. Actually, the figure shows the idealized distribution -- the actual distribution
would usually be depicted with a histogram or bar graph. The figure indicates where
the control and treatment group means are located. The question the t-test addresses
is whether the means are statistically different.
What does it mean to say that the averages for two groups are statistically different?
Consider the three situations shown in Figure 2. The first thing to notice about the
three situations is that the difference between the means is the same in all three But, you
three.
should also notice that the three situations don't look the same -- they tell very
different stories. The top example shows a case with moderate variability of scores
within each group. The second situation shows the high variability case. the third
shows the case with low...

...Last name:
First name:
Student #:
STA 304H1 F/1003H F SUMMER 2009, First Test, May 28 (20%) Duration: 50min. Allowed: hand-calculator, aid-sheet, one side, with theoretical formulas and definitions only. [25] 1) A marketing analyst is asked to study the buying habits of shoppers at a national chain store (e.g. Sears). Suppose there are 150 stores around the country. (a) Describe the population of interest. (b) Describe in short a realistic sampling procedure for obtaining a representative sample in this problem, and give a name of the procedure. (c) Are the target population and sampled population the same? Explain some related problems. (d) Give two variable of interest related to element of the population (one quantitative, the other qualitative). (e) Describe an appropriate method of data collection in this study. Solutions: [5](a) All shoppers at the chain store. More accurate definition would be: All shoppers that regularly shop at the chain store, but then it should require to defining who is a “regular shopper”. The definition may also include a time period of shopping. [5] [7](b) Two stage cluster sampling: First select an SRS of stores, and then a sample of customers, e.g. when entering the store, or at exit, using systematic sampling, because a list of shoppers does not exist. [7] Selecting customers from each store is possible but would be inconvenient and much more costly. Also, the sampling design may include a rule of selecting a...

...TEST REVIEW – We will work these problems in class. Data Files for these
problems will be disclosed in class during the review. On TEST 3, you will be
asked to perform hypothesis tests, find confidence intervals, and conduct
regression analyses. Be prepared to also interpret information on any Excel
print-outs. Test 3 will be a multiple-choice test.
1.
A federal agency responsible for enforcing laws governing weights and measures
n=1
routinely inspects packages to determine whether the weight of the contents is at least as
no population st deviation---- T test
mean ( not proportion)
great as that advertised on the package. A random sample of 18 containers whose
Ho: u=8
H1: u0
F test DA
analysis, the president decided to retain supplier A if there is sufficient statistical
evidence that supplier A’s condensers last longer on average than supplier B’s
condensers. In an experiment, 30 midsize cars were equipped with air conditioners using
type A condensers while another 30 midsize cars were equipped with type B condensers.
The number of miles (in thousands) driven by each car before the condenser broke down
was recorded. Should the president retain supplier A?
13-22
Z-TEST: PROPORTION
3.
A new credit card company is investigating various market segments to determine
whether it is profitable to direct its advertising...

...Assessing T-tests
To clearly identify what a t-test accomplishes in descriptive statistics it is imperative to understand what a t-test represents. A “t-test is a parametric statistical test for comparing the means of two independent samples” (Plichta & Kelvin, 2013, p. 464). Gosset developed the
t-test for use in quality control at the Guinness Brewery and published his works under the pen name “Student” (Plichta & Kelvin, 2013). T-tests use assumptions related to the underlying variable of study, where it is assumed that the underlying variable is distributed normally (Fagerland, 2012, p. 76). In essence, the t-test examines differences between two groups on a variable of interest.
Research Study Review
Bradley (2012), proposed to study the effects of nurse practitioners (NP’s) utilizing a skin cancer screening tool along with receiving further education on skin cancer assessment and diagnosis. The study was predicated on the Health Promotion Model (HPM), which was selected based on it relevance to the practice of NP’s and their duty to promote healthy behaviors (Bradley, 2012). “Evidence-based research showcased within the HPM can aid NPs in making practical recommendations to reduce skin cancer risk, specifically melanoma” (Bradley, 2012, p. 83). Study participants (NP’s) were provided with training and educational...

...1. A recent issue of Fortune Magazine reported that the following companies had the lowest sales per employee among the Fortune 500 companies. [20 Marks]
| |Company |Sales per Employee ($1000s) |Sales Rank |
| |Seagate Technology |$42.20 |285 |
| |SSMC | 42.19 |414 |
| |Russell | 41.99 |480 |
| |Maxxam | 40.88 |485 |
| |Dibrell Brothers | 22.56 |470 |
|a. |How many elements are in the above data set? |
|b. |How many variables are in the above data set? |
|c. |How many observations are in the above data set? |
|d. |Name the scale of measurement for each of the variables. |
|e. |Name the variables...