1. Review for Exam 2 (Ch.6,7,8,12) Ch. 6 Sampling Distribution
Despite interest in population mean (µ), most of the time we only study a sample  sample mean (x).
Central Limit Theorem - IF
the population has mean  and variance 2, and
the sample size n is large enough,
THEN: the sample mean x follows a normal distribution
BUS304 – Chapters 6, 7, 8,12

2. Ch. 7 Estimating Population Mean
The confidence interval for population mean using sample data:
when population variance known
when population variance unknown
Determining sample size (pilot sample)
BUS304 – Chapters 6, 7, 8,12

3. Ch. 8 Hypothesis Tests
Hypothesis Tests are set of methods and procedure to study the reliability of claims about population parameters
The mean price of a beach house in Carlsbad is at least $1million dollars
One tail (Upper / Lower), Two Tail
Example of Upper Tail test, population variance known (else use t distribution)
H0: μ ≥ $1million
HA: μ < $1million
H0: μ ≤ 3
HA: μ > 3
Reject when the sample mean is too high z
Decision rule
If zx > z, reject H0
If zx ≤ z, do not reject H0
BUS304 – Chapters 6, 7, 8,12

4. Ch. 12 Correlation & Regression
Examine the relationship among two or more random variables
Correlation (r)
The value will be from -1 to 1,
Measures the degree of linearity
H0 :  ≥ 0, HA:  < 0
If t < t, reject the hypothesis H0,
If t ≥ t, do not reject the hypothesis H0.
Regression Model
x (independent), y (dependent) variables, R2=r2 measure of goodness of fit
Positive Relation
yi = 0 + 1 * xi + i
BUS304 – Chapters 6, 7, 8,12