Section 1.3
Experiments and
Observational Studies
Statistics: Unlocking the Power of Data
Lock5
Outline
Association versus Causation
Confounding Variables
Observational Studies vs Experiments
Randomized Experiments
Statistics: Unlocking the Power of Data
Chapter Goals
After completing this chapter, you should be
able to:
apply multiple regression analysis to business
decision-making situations
analyze and interpret the computer output for a
multiple regression model
.
explain model building using multiple
Chapter Goals
After completing this chapter, you should be
able to:
Determine whether the correlation is significant
Calculate and interpret the simple linear regression
equation for a set of data
Understand the assumptions behind regression
analysis
.
Ca
Chapter Goals
After completing this chapter, you should be
able to:
.
Use the chi-square goodness-of-fit test to
determine whether data fits a specified distribution
Set up a contingency analysis table and perform a
chi-square test of independence
Chap 13
Chapter Goals
After completing this chapter, you should be able
to:
Understand different analysis of variance designs
Perform a single-factor hypothesis test and interpret results
Conduct and interpret post-analysis of variance pairwise
comparisons proced
Chapter Goals
After completing this chapter, you should be
able to:
Find critical chi-square distribution values from the chisquare table
Formulate and complete hypothesis tests for the
difference between two population variances
.
Formulate and complete
Chapter Goals
After completing this chapter, you should be
able to:
Test hypotheses or form interval estimates for
two independent population means
.
Standard deviations known
Standard deviations unknown
two means from paired samples
the difference betwee
Chapter Goals
After completing this chapter, you should be
able to:
Formulate a decision rule for testing a hypothesis
Know how to use the test statistic, critical value, and
p-value approaches to test the null hypothesis
Know what Type I and Type II erro
Chapter Goals
After completing this chapter, you should be able
to:
Construct and interpret a confidence interval estimate for a
single population mean using both the z and t distributions
Determine the required sample size to estimate a single
population
Chapter Goals
After completing this chapter, you should be
able to:
Define the concept of sampling error
Determine the mean and standard deviation for the
_
sampling distribution of the sample mean, x
Determine the mean and standard deviation for_the
samp
Chapter Goals
After completing this chapter, you should be
able to:
Identify the components present in a time series
Compute and interpret basic index numbers
Apply trend-based forecasting models, including linear
trend, nonlinear trend, and seasonally ad
Chapter Goals
After completing this chapter, you should be
able to:
Recognize when and how to use the Wilcoxon
signed rank test for a population median
Recognize the situations for which the Wilcoxon
signed rank test applies and be able to use it for
de
Chapter Goals
After completing this chapter, you should be
able to:
Use the seven basic tools of quality
Construct and interpret x-charts and R-charts
Construct and interpret p-charts
Construct and interpret c-charts
.
Chap 18-1
Chapter Overview
Quali
Section 1.2
Sampling from a
Population
Statistics: Unlocking the Power of Data
Lock5
Outline
Sample versus Population
Statistical Inference
Sampling Bias
Simple Random Sample
Other Sources of Bias
Statistics: Unlocking the Power of Data
Lock5
Sample v
Section 1.1
The Structure of Data
Statistics: Unlocking the Power of Data
Lock5
Outline
Data
Cases and variables
Categorical and quantitative variables
Explanatory and response variables
Using data to answer a question
Statistics: Unlocking the Power of D
Section 2.3
One Quantitative
Variable:
Measures of Spread
Statistics: Unlocking the Power of Data
Lock5
Outline
One quantitative variable:
Standard
deviation
z-score
Five-number
Range
summary
and IQR
Percentiles
Statistics: Unlocking the Power of Dat
Section 2.1
Categorical Variables
Statistics: Unlocking the Power of Data
Lock5
Outline
One categorical variable
Summary statistics: frequency table, proportion
Visualization: bar chart, pie chart
Two categorical variables
Summary statistics: two-way t
Section 2.2
One Quantitative
Variable:
Shape and Center
Statistics: Unlocking the Power of Data
Lock5
Outline
One Quantitative Variable
Visualization:
Shape:
dotplot and histogram
symmetric, skewed
Measures
Outliers
of center: mean and median
and resi
Section 2.4
Outliers, Boxplots, and
Quantitative/Categorical
Relationships
Statistics: Unlocking the Power of Data
Lock5
Outline
One quantitative variable (continued)
Formal rule for outliers
Boxplots
One quantitative and one categorical variable
Side-
Research Methods: Fall 2016
Module 15 Assignment
Due Friday, 9/30 to Moodle
Use the Excel file 240 Stats 1 Workbook to complete this assignment; save as another document. Type
your written answers into the appropriate sheet. You will need to submit this a
http:/ezproxy.stmartin.edu/login?url=http:/search.ebscohost.com/login.aspx?
direct=true&db=pdh&AN=2015-08351-001&site=ehost-live
Grossman, E. S., Hoffman, Y. G., Berger, I., & Zivotofsky, A. Z. (2015). Beating their chests:
University students with ADHD d
Chapter Goals
After completing this chapter, you should be
able to:
Construct a payoff table and an opportunity-loss table
Define and apply the expected value criterion for decision
making
Compute the value of perfect information
.
Describe the decision e
Chapter Goals
After completing this chapter, you should be
able to:
Find probabilities using a normal distribution table
Apply the normal distribution to business problems
.
Convert values from any normal distribution to a
standardized z-score
Recognize w
Chapter Goals
After completing this chapter, you should be able to:
Apply the binomial distribution to applied problems
Compute probabilities for the Poisson and hypergeometric
distributions
.
Calculate and interpret the expected value of a probability
di
Chapter Goals
After completing this chapter, you should be
able to:
Explain three approaches to assessing
probabilities
Apply common rules of probability, including the
Addition Rule and the Multiplication Rule
Use Bayes Theorem for conditional probabi
Learning Objectives
Test hypotheses and construct confidence
intervals about the difference in two
population means using the Z statistic.
Test hypotheses and construct confidence
intervals about the difference in two
population means using the t statis
Learning Objectives
Understand the logic of hypothesis testing, and know how
to establish null and alternate hypotheses.
Understand Type I and Type II errors, and know how to
solve for Type II errors.
Know how to implement the HTAB system to test
hypot
Learning Objectives
Know the difference between point and interval
estimation.
Estimate a population mean from a sample mean
when is known.
Estimate a population mean from a sample mean
when is unknown.
Estimate a population proportion from a sample
p
Learning Objectives
Determine when to use sampling instead of a census.
Distinguish between random and nonrandom
sampling.
Decide when and how to use various sampling
techniques.
Be aware of the different types of error that can
occur in a study.
Und
Learning Objectives
Understand concepts of the uniform
distribution.
Appreciate the importance of the normal
distribution.
Recognize normal distribution problems, and
know how to solve them.
Decide when to use the normal distribution to
approximate bi