a. This analysis shows the effects of different teaching styles on reading scores by using an analysis of the variation between groups and within groups. This ANOVA analysis then allows us to see how close our data is to the null. b. Null: Basal = DR
GBA462
Lecture 1.1
Events and Probability
Chapters 3.1-3.4
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.01.2016
COURSE INTRODUCTION
A foundations course in statistical analysis and
interpretation
Asking the right questions and identifying
GBA462
Lecture 2.3
Hypothesis Testing
Chapters 7.3 & 7.5-7.6
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.10.2016
CONDITIONS REQUIRED FOR A VALID
SMALL SAMPLE HYPOTHESIS TEST FOR
A random sample is selected from the target population.
The
GBA462
Lecture 2.2
Confidence Intervals & Hypothesis Testing
Chapters 6.5 & 6.7 & 7.1-7.2 & 7.4
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.09.2016
SAMPLING SIZES FROM
SAMPLING ERROR (SE)
In general, we express the reliability associated
GBA462
Lecture 1.3
Continuous Random Variables
& Sampling Distributions
Chapters 4.5-4.6 & 5.1 & 5.3
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.03.2016
PROBABILITY DISTRIBUTION FOR
CONTINUOUS RANDOM VARIABLES
Since a continuous variable
GBA462
Lecture 3.3
Two Samples Hypothesis
& Categorical Data Analysis
Chapters 8.6 & 10.1-10.4
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.17.2016
TWO POPULATION VARIANCES:
INDEPENDENT SAMPLING
Sometimes target parameter of interest could
GBA462
Lecture 3.1
Two Samples Hypothesis
Chapters 8.1-8.2
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.15.2016
DETERMINING THE TARGET PARAMETER
Simon Business School | Pre-Fall 2016 | 08.15.2016
2
TWO SAMPLES HYPOTHESIS
How would you try
GBA462
Lecture 1.2
Conditional Probability, Random Variables
& Probability Distributions
Chapters 3.5-3.7 & 4.1-4.3
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.02.2016
CONDITIONAL PROBABILITY
Event probability given that another event occ
GBA462
Lecture 3.2
Two Samples Hypothesis
Chapters 8.3-8.5
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.16.2016
TWO POPULATION MEANS:
PAIRED SAMPLING
Compares means of two different variables for a given
set of data points.
Observations a
GBA462
Lecture 2.1
Confidence Intervals
Chapters 6.1-6.4
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.08.2016
TARGET PARAMETER
The unknown population parameter (e.g., mean or
proportion) that we are interested in estimating is called
the t
BCS 200 Lab # 9 Analysis of Variance (ANOVA) Due: Friday, Dec. 15 In this lab you will use Excel to perform a one-way analysis of variance and write a brief report on your findings in Word. The problem: Researchers at Purdue University conducted an e
Lab_07 November 29, 2006
Correlation between Brain Size and IQ for High IQ Subjects 144
142
IQ of High IQ Subjects
140
138
136
134
132
130 7.5
8
8.5 9 9.5 10 Brain Size of High IQ Subjects
10.5
11 x 10
5
Part A:
With this data, we can d
Lab: Wednesday 12p November 15, 2006
0 -0.1 -0.2 -0.3 -0.4 -0.5 -0.6 -0.7 -0.8 Average Improvement Test Group for Visual Sensitivity in Amblyopes Control Group
Test group: -1.00 -1.31 0.09 -2.87 -0.57 -0.10 -0.26 -0.42 -0.95 -0.32 Control group: -
Lab 08 December 5, 2006
A linear model using the equation, Y = a + b * x, was used so that we could construct a best fit model. Threshold #1: - r =-0.8437 - a =10.5311 - b =-1.1498 - MSE = 4.2378 This linear model shows the highest mean squared erro
GBA462
Lecture 4.1
Simple Linear Regression
Chapters 11.1-11.4
Sercan Sarigul | Simon Business School | Pre-Fall 2016 | 08.22.2016
MODELS
Representation of some phenomenon
- Force (Newtons 2 Law), monthly sales, stock prices.
Mathematical model is a mat