Psychology 104
Dr. Claire Scavuzzo
scavuzzoC@macewan.ca
Lets pull up the syllabus
Syllabus on blackboard
2 midterms and a final
Multiple choice, short answer, matching
Research participation
Look on blackboard for Handout
Asking questions/speaking o
Pseudoscience
Set of claims that
seems scientific
Confirmation bias
Belief perseverance
Even though
circumstantial evidence
against
Testable claims
Often with weak or non
existent evidence
Warnings of pseudoscience
http:/www.vice.com/en_ca/video/wat
Stat 151: Introduction to Applied Statistics
Lecture 1
Instructor:
Brian Franczak
Section AS06
CCC 5-158
MacEwan University
September 8, 2016
Todays Lecture
We have quite a bit to do today!
We will proceed in the following order:
1. We will review the key
Early history of psychology
Early history of psychology
Informal attempts for 1000s
yrs
Hard to distinguish from
philosophy
Rely laregly on common sense
Psychology= study of the
psyche
Most efforts in spiritualism
Psyche= soul or spirit
Early attem
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Solution of Assignment #7
Instructor: A. Simchi
Question #1:
(a) The least-square line of SBP (Y ) on QUET (X) for Smokers and nonsmokers
are:
Non smokers : SBP = 49.312 + 26.303 QU ET
Smokers : SBP = 79.255 + 20.118 QU ET
(b) Let The single multiple mode
Solution of Assignment #4
Instructor: A. Simchi
Question #1:
(a) The least-square estimate of the regression line when Y regressed on X1 is:
Y = 70.42020 + 227.09370 X1
Based on the computer output on pages 1 and 2, we have R2 = 0.9194 and
2
rY X1 = 0.958
Solution of Assignment #2
Instructor: A. Simchi
Question #1:
(a) The least-square estimate of the regression line when Y regressed on X is:
Y = 1.69956 + 0.83991 X
The change in the mean response when X increases by one unit is just 1 .
Therefore, the est
Solution of Assignment #6
Instructor: A. Simchi
Question #1:
(a) The plot of Y versus X is given on page 1 of SAS output. It is clear that a
straight line model is not adequate. By looking at the graph, it seems that the
1
transformation X or ln(X) is mor
Stat 378/502 Al Midterm Exam Name: S 911%.; i 0 \n Kc at
October 28, 2005 Student No: Q 1; 4; 3 g 53
Page 2 of 4
1. Consider the following model:
Y=0+B1X1+ZX2+B3X3+E
(1 m q Hap) What is the Adjusted R2? {,LD
R9. MSW , I 31%.212/33 : a, 1?;
Mia r ml 403.
-10 0 10 20 30 40 50 60
Degreedays
Gas = 1.0892108 + 0.188999 Deree-days
RSquare 0.99055
FlSquare Adj 0.989875
Root Mean Square Error 0.338928
Mean of Heeponse 5.30625
Observations (or Sum Wgts) 16
Source DF Sum of Squares Mean Square F Flaiio
M
Ken's Comments Based on a Light Reading of Labs #6 1. The lab asked for plots of residuals vs. each predictor in the final model. Most people included plots of leverage residuals vs. each predictor in the final model. Leverage residuals and residuals are
Descriptive Measures
Instructor: Wanhua Su
STAT 151, Covers Chapter 3 from the Textbook
In the last note we talked about the shape of a distribution: bell shaped or others, unimodal or multimodal, symmetric or skewed. Now, we will discuss how to describe
Inferential Statistic
The objective of inferential statistics is to use sample data to obtain results about the whole
population.
In a rst step the goal is to describe an underlying population. Since the populations are described in form of models, that a
1
Analysis of Categorical Data
The techniques presented in previous sections cover the analysis of numerical data and variables. Up to now it is left unanswered how to analyze categorical variables and data.
1.1
Two-way tables
How to present data for cate
1
Inferential Methods for Correlation and Regression
Analysis
In the chapter on Correlation and Regression Analysis tools for describing bivariate continuous
data were introduced. The sample Pearson Correlation Coecient and the sample Regression
Line were
1
Hypotheses test about if is not known
In this section we will introduce how to make decisions about a population mean, , when
the standard deviation is not known. In order to develop a condence interval for estimating
and a test we need to study the sa
1
Inferential Statistics for Proportions
1.1
Hypotheses test about a Population Proportion p
Instead of answering questions concerning a population mean, , we now want to answer
questions about a population proportion, p.
Is the proportion of voters who s
1
ANOVA
ANOVA means ANalysis Of VAriance.
The ANOVA is tool for comparing the means of more than two populations. These means can
be inuenced by dierent factors.
Example: A local school board is interested in comparing test scores on a standardized readin
1
Probability Theory
1.1
Experiment, Outcomes, Sample Space
Example 1 An psychologist examined the response of people standing in line at a copying
machines.
Student volunteers approached the person rst in line and asked for permission to skip line,
becau
1
Organizing and Graphing Data
1.1
Organizing and Graphing Categorical Data
After categorical data has been sampled it should be summarized to provide the following
information:
1. Which values have been observed? (red, green, blue, brown, orange, yellow)
1
Sampling Distributions
1.1
Statistics and Sampling Distributions
When a random sample is selected the numerical descriptive measures calculated from such a
sample are called statistics. These statistics vary or change for each dierent random sample
you
Read chapters 8 and 9 in the text book.
1
Sampling
Descriptive versus Inferential Statistics
So far we assumed to have some data available and we discussed how such data should
be properly summarized. This is called descriptive statistics.
In the upcomin
1
Introduction
Course Outline
Preferred way of contact: Email
Assignments: check schedule! Hand in in class! Do it yourself!
Book: All assignments are taken from the text book. This is a good source of information
and helps to do the assignments.
Do s