KIN 371 Study Guide Midterm 1
Define the following terms
Z-score
inferential statistics
sampling error
standard error of the
mean
central limit theorem
level of confidence
skewness
kurtosis
a standard
KIN 371 Study Guide Midterm 1
Define the following terms
Z-score
inferential statistics
sampling error
standard error of the
mean
central limit theorem
level of confidence
Skewness
kurtosis
1.
If you
KIN 371
Lohse
1
11/4/14
Name:_ANSWER KEY_
Homework #3: Z-scores and the normal curve.
1. For a population with = 90 and = 25, find the corresponding z-score for the following x
values:
X = 95
.2
X = 1
Student Number: _
Page 1 of 7
PART I: Multiple Choice (15 marks; 1 mark per question)
For the following questions, choose the most accurate/best option and write the option letter in
the answer sheet.
YOUR NAME: _
KIN 371-002
Final Exam
Student #: _
Fall 2013
You may use scratch paper and a calculator. You can also use your book and notes. SHOW
YOUR WORK when appropriate. CIRCLE YOUR FINAL ANSWERS.
1
KIN 371 Pre mid-term MC sample questions
Choose the most accurate / best option.
1) Adding a constant to every score in the data will cause the distribution curve to:
a) shift/move, but the curve st
Chapter 5
Multiple correlation and multiple regression
The previous chapter considered how to determine the relationship between two variables
and how to predict one from the other. The general soluti
Complete
Chapter 10
Ch 8 deals with nding CI and performing hypothesis tests on a single population
mean (1-sample) and comparing 2 population means.
Ch 10 is an extension and deals with comparing mor
Newsom, USP 634 Data Analysis I, Spring 2013
1
Factorial ANOVA for Mixed Designs
Notation
In the following hypothetical example, I examine the effects of the educational context on vocabulary in 5th
g
Page 1
HKIN 371 Problem Set 7
Multiple regression
Question 1 (hint: use a Venn diagram)
A) Given that the shared variance between X1 and X2 is greater than 50%, and the shared
variance between X2 and
Lecture 11:
One Way ANOVA
Repeated Measures
Laura McAvinue
School of Psychology
Trinity College Dublin
Analysis of Variance
One way ANOVA
Factorial ANOVA
One Independent
Variable
More than One
Indepen
Page 1
HKIN 371 Problem Set 4
t-Tests, power, effect size
1) Define the following terms:
a) Standard error of the difference (SED)
b) Power
c) Effect size
2) List four assumptions of the t-test.
3) A
Page 1
HKIN 371 Problem Set 5
Simple ANOVA, post-hoc analysis
1)
Source of
variance
SS
df
MS
F
p
Between groups
_
1
_
_
_
Within groups
21.7
_
1.206
Total
52.95
_
a)
b)
c)
d)
Fill in the missing value
Lecture 11:
One Way ANOVA
Repeated Measures
Laura McAvinue
School of Psychology
Trinity College Dublin
Analysis of Variance
One way ANOVA
Factorial ANOVA
One Independent
Variable
More than One
Indepen
Lecture 11:
One Way ANOVA
Repeated Measures
Laura McAvinue
School of Psychology
Trinity College Dublin
Analysis of Variance
One way ANOVA
Factorial ANOVA
One Independent
Variable
More than One
Indepen
Parametric Hypothesis testing
Does our sample mean differ
from population mean?
Do our sample means differ
from each other?
Do we know the
population standard
deviation?
Yes
Are the samples independen
Repeated Measures
ANOVA
Quantitative Methods in HPELS
440:210
Agenda
Introduction
The Repeated Measures ANOVA
Hypothesis Tests with Repeated Measures
ANOVA
Post Hoc Analysis
Instat
Assumptions
In
Chapter 8
Correlations:
Relationships among
variables
Recall: Statistics
Statistics is a mathematical technique by
which data are organized, treated, and
presented for interpretation and
evaluation.
S
Page 1
KIN 371 Problem Set 9
Factorial ANOVA
1. A nutritionist conducted a study in which every participant consumed daily doses of a
dietary supplement or a placebo (factor = drug), and were prescrib
KIN 371:
Introduction to Statistics in
Kinesiology
www.ubc.ca
Thenextweb.com
Classes 17, 18, & 19: Testing
One Sample Mean
February 10, 15, & 17, 2017
ubyssey.ca
Digitalspy.co.uk
KIN 371: Introduction
Chapter 8
Estimating the Mean of a population
When the population mean is unknown and we have a sample mean, it is referred to as a point
estimate.
Confidence interval- range or interval of values tha
Chapter 6
Probability
Probability- How likely is a particular event to occur in comparison to all possible outcomes
P(event) = # of ways/ total # of possible outcomes
The addition rule - the combined
Chapter 9
Inferential Stats: Testing the difference between paired means:
Within Groups:
Each research participant appears in both levels of the independent variable rather than just one
This is an ex
Chapter 7
Testing One sample mean
Inferential Statistics- taking the sample data and making inferences on the larger population.
Inferential stats enable us to test the hypotheses
We normally do not k
Chapter 10
Type I error: The risk in rejecting the null hypothesis
We begin hypothesis testing with the assumption that the null hypothesis is true, meaning the
hypothesized effect or relationship doe
Page 1
KIN 371 Problem Set 8
Repeated-measures ANOVA
1. Below is the output of a one-way repeated-measures ANOVA. Besides the fact that
between-subjects information is left out, some within-subjects i
THE UNIVERSITY OF BRITISH COLUMBIA
SCHOOL OF KINESIOLOGY
KIN 371: INTRODUCTION TO STATISTICS
2014 Winter Section 002
Instructor:
Class:
Office hours:
Nicole Ong (Email: [email protected])
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ANOVA factory
Making stats awesomer since 1918
What is Factorial ANOVA?
Multiple independent variables
Recall: Fa