Exam 2
Alternative Hypothesis:
What you suspect is true
Always stated in terms of a population parameter
HA : u > 0.545 degrees
A statement that the population parameter (e.g. mean,
proportion, standard deviation) somehow differs to some
claimed value
Chapter 2
Frequency Distribution (Table)
*Definition: a table that lists datavalues along with their corresponding
frequencies (or counts).
*Frequency tables help us understand the nature of our data
*These help us
+summarize large datasets
+gain insight
H0=0.26
HA#0.26
pvalue=0.03
Chi Square Test:
alpha=0.5
reject the Null
There is strong evidence the pop st deviation is not 0.26
H0=o1 square=o2 square=o3 square=.=on square
Borthett test
H0=u1=u2=u3.un
ANOVA test
H0=median1=median2=median3=median n
HA:
Math 159 Quiz 6
Chapter 6 Study Guide:
Understand the relationship between random sample statistics and
probability distributions (i.e. the most important slide in Ch 6)
Sample statistics (like the sample mean or the sample standard deviation) are
contin
Math 159 Quiz 5
Chapter 5 Study Guide:
Define a Random Variable:
A function that can assign an unique numerical value, determined by
chance, for each outcome of a procedure.
Examples: rolling a die, flipping a coin, etc.
Define a Discrete Random Variabl
The Chapter 3 quiz has some questions were you have
to write down the answers
(NOT all TrueFalse or Multiple Choice questions):

Definition of the Standard Deviation:

Definition of a Percentile:

A statistic or parameter used to measure the amount of
Math 159
Chapter 2 Quiz
 Know what type of data is used in a histogram : quantitative data.
 Know what type of data is used for a Pareto chart : qualitative data.
 Know rules for good graphs (including that on a graph you should identify
any
suspected
Math 159 (Statistics) Class
Chapter 1 Quiz
Definitions for these terms:
?
Quantitative or numerical data: data
consisting of number representing values, counts or
measurements. Ex: height, weight, blood pressure
+ Discrete data: a type of quantitative dat
Math 159 Exam 1
Percentile: The 99 values that divide a ranked (sorted) dataset into 100 groups with
approximately 1% of the values in each grouping.
Probability:
A number between 0 and 1 (inclusive) that measures the likelihood of an event.
Example 1:
Math 159 Final Exam Study Guide
Chapte
r
1
1
1
1
1
1
1
Topic
Know Good / Bad uses of statistics (e.g. too small a sample is
bad, a haphazard sample is bad for inference, etc.)
Qualitative and Quantitative Data
Qualitative (or categorical) data: also calle
Exam 2 Study Guide  Math 159
Term / Concept
Alternative Hypothesis
ANOVA
Bartlett's Hypothesis Test
Binomial Distribution
Central Limit Theorem
Chi Square Hypothesis Test
Confidence Interval
Confidence Level of a Confidence Interval
Expected Value of a P
Tho Au
Microeconomics
Professor: Tina Mosleh
Stock Assignment
12/05/2012
Stock Paper
After doing some research online, I have decided to invest all my money ($10,00) into Cisco
Stock because there are many Ciscos attractive features for investors.
I
was l
Chapter 13
Non Parametric Hypothesis Tests
Parametric Hypothesis Test Definition
Hypothesis Tests which have requirements about the nature or share of the
populations involved
Very commonly used
Examples include:
 Z tests
 T tests
 ANOVA
 Chi Square T
Chapter 12
The ANOVA Hypothesis Test
A hypothesis test for comparing the equality of 2 or more means
Alternative Hypothesis: at least one mean is different from the others
Null Hypothesis: the means are equal
Obtain a pvalue
Small pvalue (less than your
Chapter 10
Scatterplot: a graphical display of paired quantitative data used
to look for outliers or relationships between the variables
Correlation coefficient: a statistic or parameter that measures
the strength and direction of the linear relationship
Chapter 9
Hypothesis Testing for 2 Samples
Two Sample Hypothesis Test for Means
Ho: u1=u2
HA: u1 =/ u2 (or > or <)
Two samples are independent if the sample values from one population are not
related to or somehow naturally paired or matched with the samp
Chapter 8
Hypothesis Test
A tool of statistic inference
Used when you want to make a statement or decision about population parameter
using a random sample
Can be performed for ay population parameter using a random sample
Also called Significance Tests
N
Chapter 7
Tools of Statistical Inference Part 1
Confidence Intervals
Point Estimate:
One tool of statistical inference
A single value from a random sample (a statistic like xbar or s) used to estimate a
population parameter (u, o, P, etc)
Examples:
 Bre
Chapter 6
Continuous Probability Distribution
Theoretical Continuous Probability Distributions
Non discrete equivalents of what we studied in Chapter 5
Answers the problemwhat to do when dealing with continuous random
variables in which the outcomes are
Chapter 5
Discrete Probability Distributions
Function
A mathematical rule that provides exactly one output value for each input value
X= 5; f (x)= 2*x => f (5) = 2*5 = 10
A function that can assign an unique numerical value, determined by chance, for
each
Chapter 3
Common Statistics and Parameters
Measure of Center
*Arithmetic Mean (or Arithmetic Average)
 A statistic (or parameter), which measures the center of a dataset by adding the values in
a dataset and then dividing by the number of values in the d
Chapter 2
Frequency Distribution (Table)
*Definition: a table that lists datavalues along with their corresponding frequencies (or
counts).
*Frequency tables help us understand the nature of our data
*These help us
+summarize large datasets
+gain insight
Chapter 13 Study Guide:
Know the definition of a Nonparametric Hypothesis Test
Hypothesis Test which have no requirements about the nature or
share of the populations involved (e.g. do not require Normal shaped
data)
Very often called distributionfree
Chapter 10 Study Guide:
Define the term scatterplot:
Scatterplot: a graphical display of paired quantitative data used to look for outliers or
relationships between the variables.
Define the term regression analysis:
Regression Equation: a type of algebra
Chapter 8 Study Guide:
Be able to interpret the results of a hypothesis test. If given a scenario and a pvalue be able to:
o Tell me if should reject or accept based on the pvalue and the alpha lelvel
P value less than alpha reject, P value large than
Chapter 7 Study Guide:
Define Alpha error for a confidence interval
The chance that your confidence interval does not overlap the true unknown population
parameter
The failure rate of the confidence interval process
Example: The confidence level is 90%