02/11/2014
From chapters 2 7, we focused on the
descriptive statistics
Descriptive statistics is concerned with techniques that are used
to describe or characterize the obtained data (page 10)
Chapter 8
Random sampling
and probability
We learned different
THIS EXAMINATION WILL NOT BE DEPOSITED IN THE LIBRARY RESERVE
NOTE: This practice exam is designed to give you some idea of what to expect. It is
NOT intended as a template for the actual exam this year. It might somewhat similar, but
make no guarantees.
Practice Test One PSYC 2F23
PRACTICE TEST
This is an open book test. You may use calculators, notes, textbooks, homework etc,
however, you may NOT use old tests or exams
You MAY NOT use lap top computers.
There is also NO sharing of materials or calculato
Course: Psyc 2F23
Initials:_ ID_Page 1 of 13
Practice Progress Exam number TWO
Note: I have removed the multiple choice questions
(sorry, but there are just so many I have to choose from so I cannot put them all out there)
Not all answers are shown either
01/02/2015
For all the tests we have learned so far (single sample
z, single sample t, correlated t, and independent t
tests, we have been using the MEAN as the basic
statistic for hypothesis testing.
Chapter 15
Introduction to the Analysis of Variance
(A
25/02/2015
Recall: for independent t test (Chapter 14)
One independent variable (IV) with 2 conditions
For example:
Chapter 16
Introduction to Two-Way Analysis of
Variance (two-way ANOVA)
IV : the type of cell phones (iPhone vs. Galaxy)
DV: how much peopl
18/01/2015
From Chapter 12, we learned how to test hypothesis
using single sample z test
The research typically involves:
a single sample (N) that represents a real
population, which may indicate some effect of I.V.;
the mean of the sample is X
Chapter 1
23/01/2015
So far, we have learned how to test hypothesis, using
three different tests including:
Sign test (Chapter 10)
Single sample z test (Chapter 12)
Single sample t test (Chapter 13)
Chapter 14
Students t test for correlated and
independent group
15/03/2015
The non-parametric tests that we will learn:
Chi-square ( ), learned previously in Part I.
2
Chapter 17
Chi-square and other nonparametric tests
Wilcoxon matched-pairs signed ranks test: the
non-parametric version of the correlated t test
Ma
06/03/2015
Parametric tests vs. non-parametric tests
What is a parameter?
Chapter 17
Chi-square and other nonparametric tests
In Chapter 1, we learned that a parameter is a number
calculated on population data that quantifies a
characteristic of the popul
06/01/2015
From Chapter 10, we learned sign test for hypotheses testing
e.g., does the type of materials (e.g., pictures vs. words) influence
peoples memory?
Correlated groups design
Chapter 12
Sampling distributions, Sampling
Distribution of the Mean, th
03/01/2015
e.g., is there a difference between two types of cola (brand X;
brand Y) in how much people like them?
H1: X Y
H0: X = Y
Hypotheses:
18 like X, and 2 like Y
Result:
(N=20)
Chapter 11
Power
Possible explanation
of the result:
X Y (H1)
(and it lo
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Chap 9 page 1
Chap 9 page 2
Chap 9 page 3
Chapter 9
Binomial Distribution
Binomial Distribution
e.g. flipping a coin
1) N trials can be any number of trials
1) N trials
2) only 2 outcomes heads or tails
2) only 2 outcomes
3) outcomes mutually exclusive ca
07/09/2014
A consumer survey
(sample size, N = 100)
How much do you like our product on a scale of 0 100?
Data:
Chapter 3
Frequency Distributions
8,83,9,42,26,10,51,98,96,23,94,88,25,77,4
4,6,16,71,84,20,13,91,15,41,93,58,97,17,7
3,38,3,90,55,78,73,76,81,
Psychology 2F23 Midterm Test
SECOND practice test ONE
This is an open book test. You may use calculators, notes, textbooks, homework etc,
however, you may NOT use old tests or exams
You MAY NOT use lap top computers.
There is also NO sharing of materials
07/09/2014
Some notation
Variables
X, Y, A, B, etc
Chapter 2
Basic Mathematical and Measurement Concepts
A particular score of a variable
X1, X2, X3 Y1, A1, B1, etc
Some notation
Table 2.1 Age of Six Subjects
Subject
Number
1
Score
Symbol
X1
Score Value,
21/09/2014
Chapter 5
The normal curve and standard
scores
Y
(Frequency)
The normal curve
(normal distribution)
X (Score)
Y
N
e
2
X 2
2 2
Y = frequency of a given value of X
X = any score in the distribution
= mean of the distribution
= standard deviat
09/11/2014
Lets consider the following question:
If I flip a fair coin 10 times, what are the possible
outcomes?
Possible outcomes:
Chapter 9
Binomial Distribution
0 tail, 10 heads
1 tail, 9 heads
2 tail, 8 heads
8 tail, 2 heads
9 tail, 1 head
10 tail, 0