Homework Assignment #2
(Due by Feb. 29, 2012)
1. Below are the data for the number of different word roots that normal children (20
month old) generated when their parents believe they were placed in the most
comfortable situation (e.g., after meal, befor
Homework assignment #4
(Due by April 18, 2012)
* Use Table A on page 470 in the textbook for questions 1-3 and Table B on page
472 for questions 4-5 (two-tailed tests).
* For questions 4-5, if you cant find the exact df in the table, use the closest value
Homework assignment #3
(Due by March 7, 2012)
1. John has taken an SAT test that consists of two sections (verbal and math). He scored
580 on verbal and 610 on math test, respectively. John later learned that the means
and standard deviations of the score
You and your friend decide to get your cars inspected. You are informed that 84% of cars pass inspection. If the event of your car's passing is independent of
your friend's car,
a) What is the probability that your car passes inspection?
b) What is the pr
Introduction to SPSS
Week 2
February 9, 2015
Introduction to SPSS
Why SPSS?
Powerful tool for data management & analysis
Compatibility with advanced stat programs
such as EQS, LISREL, etc.
Other stat packages other than SPSS?
SAS, SYSTAT, SIX SIGMA, etc.
Data Presentation & Central
Tendency
Week 2
February 11, 2015
Overview
Frequency distribution (Chapter 2)
Data presentation
Characteristics of distribution
central tendency, variability, skewness, kurtosis
Central tendency (Chapter 3)
mean, median,
Introduction to Statistics
Week 1
February 4, 2015
Overview of todays class
The usefulness and importance of statistics
Two broad categories of statistics:
Descriptive and inferential statistics
Scales of measurement
Variables vs. constant
Summation
Statistics for Social Science (STA
2100)
January 28, 2015
Introducing yourselves
(Also tell us what you think of stat)
The Purpose of the class
Enjoy the pleasure and convenience of
using statistics
Learn basic concepts of descriptive and
inferential st
Correlation
Week 7
March 11, 2015
Overview
The Pearson Product-Moment Correlation
Coefficient
Properties of the correlation coefficient
Sampling factors that change the r
Causality and Correlation
The Pearson PM Correlation
Regression vs. Correlation
Regression
Week 6
March 4, 2015
Overview
Linear relationships
Regression constants
Regression line
Standard error of estimate
Introduction to Regression
Questions:
Can SAT scores predict college grades?
What will be the proportion of ethnic minority in
Indicators of Relative Standing
Week 5
February 25, 2015
Overview
Percentiles
Changing the properties of scales
Standard scores
Normal distribution
Percentiles
Questions:
A score of 80 on a math test: Good or poor?
A height of a man is 5-8: Tall or short?
Introduction to Hypothesis
Testing: Terminology and Theory
Week 10
April 13, 2015
Overview
Statistical Terminology: Formal
terminology and procedures
Hypothesis Testing
Example: Short-term memory
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Example: New Memory Boosting
Drug (Ginseng
Variability and
Exploratory Data Analysis
Week 3
February 18, 2015
Overview of todays class
Indicators of variability
Populations and samples
Stem-and-leaf displays
Resistant indicators
Indicators of Variability
Variability: the extent to which the scores
Elementary Techniques of
Hypothesis Testing
Week 11
April 15, 2015
Overview
Inferences about the differences between
two group means
Inferences about correlation coefficients
A comparison of the differences between
means and correlation
Statistics in
Sampling, Sampling
Distributions, and Probability
Week 9
March 30, 2015
Overview
Methods of sampling
Sampling distributions and Sampling errors
Probability and Its Application to
Hypothesis Testing
Estimation
Methods of Sampling
Examples:
Ex) Ginsen
Simple Analysis of Variance
Week 13
April 27, 2015
Overview
Logic of the Analysis of Variance
Computational Procedures
Comparisons between Specific Means
Size of Relationship
Logic of Analysis of Variance
Example: Survey on life satisfaction among
Englan
Review Session
Week 7
March 18, 2015
Chapter 1: Study of Statistics
Descriptive vs. Inferential statistics (concepts)
Measurement: assignment of numbers to attributes
of an object or an event
Scale of measurement
3 properties: magnitude, equal intervals,
In a large Business Statistics class, the professor has each person select stocks by using computer-generated random
numbers. The stocks were from a Journal in which exactly half the publicly traded stocks went up and half went
down. The students then che
When the probability comes from the long-run relative frequency of the event's occurrence, it is an empirical probability.
When the probability is subjective and represents your personal degree of belief, it is called a personal probability.
0.3/0.5 <>0.5
The P-value is more a measure of surprise than it is a measure of certainty.
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10 | P a g e
11 | P a g e
12 | P a g e
13 | P a g e
Z=0.845>0.05, fail to reject
14 | P a g e
3. (N=36) Mean of Boys: 108.1285 Standard Deviation17.11814
(N=30) Mean of Girls: 118.7226 Standard Deviation14.88106
A] H0: The full IQ between boys and girls will be the same.
H1: The fill IQ between boys and girls will be different.
Assumptions: Random