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Lecture 11

PSYC 210 Lecture Notes - Lecture 11: List Of Statistical Packages, Standard Deviation, Scatter Plot


Department
Psychology
Course Code
PSYC 210
Professor
Snjezana Huerta
Lecture
11

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PSYC 210 (2017) Assignment 2 -- p. 1 -- Due: March
27
, 2017, at 2:30 p.m.
Please submit on time to avoid late penalties.
**S
EE
O
VERALL
I
NSTRUCTIONS
in CANVAS (in announcement and on Assignment page)**
answer in order, show work, draw graphs yourself, provide explanations, use own words, cite, no plagiarism, no statistical software
round probabilities to the thousandths in your final answers
1. [2 points] In your own words, explain the connection between the relative frequencies that represent
a set of scores and the probabilities that are based on them.
2. [3 points] Imagine we surveyed 64 people, whom we asked to indicate how happy they were with
their dentist; the relative frequencies of the 8 possible responses are tabled below. Given we only
followed up with the respondents who indicated some dissatisfaction (i.e., we excluded anyone who
said they were at least a little happy and those without dentists), what is the probability associated
with randomly drawing 3 respondents with mixed feelings?
-- n/a --
no dentist
-3
very
unhappy
-2
moderately
unhappy
-1
a little
unhappy
0
mixed
feelings
1
a little
happy
2
moderately
happy
3
very
happy
.23438 .04688 .14063 .07813 .12500 .07813 .10938 .18750
3. [2 points] Imagine that 36% of our population didn't work at all on January 1 and 42% of the
population worked a longer shift than usual to accommodate others taking the day off. What is the
probability of randomly selecting someone from this population who worked but not a longer shift
than usual?
4. [4 points] Assuming a population of 11,605 X scores that are normally distributed with a mean of
216 and a sum of squared deviations of 3,992,625, how many individuals would be expected to have
an X score between 178 and 208?
5. [2 points] Imagine we are working with a normally distributed X variable with a mean of 132 and a
standard deviation of 13. What are the two X scores that contain the inter-quartile range (i.e., that
mark its beginning and its end)?
6. [3 points] Assume that we are working with a population of X scores with a mean of 78 and a
variance of 144. If we only sample from amongst the scores in the inter-quartile range, what is the
probability that we will randomly select someone with has an X score of 81 or higher?
7. [2 points] Imagine that research suggests that blurry vision is a side effect of pain reliever "Pain-B-
Gone " 1% of the time. How does this relate, if at all, to the probability that person "S" will develop
blurry vision in response to taking "Pain-B-Gone"? Explain/justify your answer.
8. [3 points] In your own words, explain [in reasonably broad strokes] how a sampling distribution is
constructed and how this relates to the notion of sampling error. As part of your explanation, be sure
to clearly define each of these two central concepts.
9. [18 points] Using the material we've covered in Topics 4b and 5a,
calculate, compare, and discuss the power associated with each of the following 6 scenarios*:
part
null hypothesis is:
the population mean...
true population
mean (µ
X
) is...
population
variance (σ
X
2
) is...
alpha
(α) is...
sample
size (n) is...
a) equals 150 155 121 .05 36
b) exceeds 150 180 121 .05 36
c) equals 150 180 81 .05 36
d) equals 150 180 121 .01 36
e) equals 150 180 121 .05 1,000
f) equals 150 150 121 .05 36
*Important: If you have to choose between two z values, choose the one associated with a
more conservative alpha value.
*For each of the 6 scenarios, provide the resulting probability and any calculations,
as well as a quick sketch of each true distribution representing approximately where the
probability associated with power would be located [i.e., which area(s) under the curve].
*Also, summarize your results/findings: describe and discuss/explain what power is
and how and why the probability was impacted ...or, if it wasn't, how/why not.
Tip: Organize
your answers
using a table
normally-distributed
^
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