i need help with questions 2, 3 and 4? Thats all. Thanks

HLST 2300 Exam Review (for Lecture)
1. Fill in the following table with the name of the statistical test:
Parametric

Non-Parametric

1 group
independent

repeated

independent

repeated

2 groups

3 groups

2. Based on the following statements, determine which statistic test is most appropriate:
STATEMENT
a) Are there significant differences in happiness ratings (ordinal) among youth (n= 50),
adults (n= 25) and seniors (n= 30)?
Youth: skewnesshappiness= 1.561
std error skewnesshappiness= 0.74
Adults: skewnesshappiness = -0.561
std error skewnesshappiness = 0.074
Seniors: skewnesshappiness = -0.561
std error skewness happiness = 0.074

Statistical test

b) Are there significant differences in weight (lbs) before and after a weight loss
intervention in a sample of 100 participants?
Pre-intervention: skewnessweight= 1.561
std error skewness weight= 0.74
Post-intervention: skewnessweight = -0.561
std error skewness weight = 0.074
c) Are there significant differences in annual income ($) between university (n = 100)
vs non-university educated workers (n = 100)?
University educated: skewnessannual income = 1.561
std error skewness annual income = 0.74
Non-university educated: skewnessannual income = -0.561
std error skewness annual income = 0.074
d) Are there significant differences in annual income ($) between university-educated
(n = 19) vs non-university educated (n = 25) workers?
University educated: skewnessannual income = 1.561
std error skewness annual income = 0.74
Non-university educated: skewnessannual income = -0.561
std error skewness annual income = 0.074
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e) Are there significant differences in annual income ($) between university-educated
(n = 39) vs non-university educated (n = 25) workers?
University educated: skewnessannual income = 1.561
std error skewness annual income = 0.74
Non-university educated: skewnessannual income = -0.561
std error skewness annual income = 0.074
f)

Are there significant differences in annual income ($) between university-educated
(n = 29) vs non-university educated (n = 25) workers?
University educated: skewnessannual income = 0.561
std error skewness annual income = 0.74
Non-university educated: skewnessannual income = -0.561
std error skewness annual income = 1.074

g)

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3. 500 participants are recruited to a study assessing patient preference for 4 different flavours of cough medicine. The
following preferences were observed:
flavour A ? 12
flavour B ? 217
flavour C ? 100
flavour D ? 171
a) If all the medicines are equally palatable, fill in the following contingency table:
Flavour A

Flavour B

Flavour C

Flavour D

Observed
Expected
2 calculation
(calculate to
two decimal
places)

b) Calculate the 2 statistic based on the above contingency table:

c) What test would you perform in SPSS to decide how likely the difference between observed and expected
frequencies are due to chance?

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4. The following table (observed frequencies) comes from a fictional study investigating the link between breast feeding
and depression in adulthood:
Breast fed
Not breast fed
Non-depressed
730
670
Depressed
85
140
a) How many depressed breast fed adults would you expect if the null hypothesis was true?

b) What test would you perform in SPSS to decide whether the distribution of depression is the same among
breast fed and not breast fed populations?

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5. A study is run to estimate the association between exposure to lead paint in childhood and attention-deficit
hyperactivity disorder (ADHD). Data on n=400 children are collected and data on exposure and ADHD diagnosis are
shown below.
Exposure to Lead Paint
Yes
No

ADHD
34
29

No ADHD
71
266

a. Calculate the risk ratio.

b. Calculate the odds ratio.

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6. An open label study (where participants are aware of the treatment they are taking) is run to assess the time to pain
relief following treatment in patients with arthritis. The following linear regression equation is estimated relating
time to pain relief measured in minutes (dependent variable) to participant?s age (in years), gender and severity of
disease (a score ranging from 0 to 100 with higher scores indicative of more severe arthritis):
Predicted Time to Pain Relief = -19.80 + 0.50*Age + 10.90*Male Gender + 0.20*Severity
a) What is the predicted time to pain relief following treatment for a female aged 50 with a severity of disease
score of 60?

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7. Obesity is a growing problem around the world. Surprisingly, some people don?t gain weight even when they
overeat. Perhaps fidgeting and other ?nonexercise activity? (NEA) explains why some people may spontaneously
increase nonexercise activity when fed more. Researchers deliberately overfed 16 healthy young adult
volunteers for 8 weeks. They measured fat gain (in kg) and, as an explanatory variable, change in energy use (in
calories) from activity other than deliberate exercise ? fidgeting, daily living and the like. From the raw data, we
find that the mean and standard deviation for the two variables are

Mean
Standard deviation

NEA change
324.75
257.66

Fat gain
2.388
1.139

The correlation between them is r = -0.779.
a) Calculate the least-squares regression line.

b) State in words what the slope of the line tells you specifically for this question.

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