Chapter 10 Review
Vocabulary

Null hypothesis
Claim about population that is initially assumed to be true
Statement of equality

Alternative hypothesis
Competing claim that we search for evidence for
Statement of inequality

Test statistic
Calculated z / t value

P-value
Probability of this sample statistic or one more extreme occurring
assuming that the null hypothesis is true

Significant
When p<α  our sample statistic probability did not happen by random
chance, but instead we believe alternative to be true
Error

Type I Error
Error of rejecting null when null is true
Denoted by α, significance level
Always remember CONTEXT!

Type II Error
Error of failing to reject null when null is false
Denoted by β
Remember that as α increases, β decreases.
Would you prefer a test with α=0.01 or α=0.05?
Power

Power
Probability of correctly rejecting the null
When H0 false, power = 1 - β
Factors that affect Power:

Sample size

Significance level

Discrepancy between hypothesized value and true value
The larger any of these three are, the higher the
power
PHANTOMS
P – parameter
H – hypothesis
Remember to describe both in context of problem
A – assumptions
N – name
Test name, α, table, tails, df (if applicable)
T – test statistic
O – output
For conclusion, remember that your decision is in
terms of ALTERNATIVE. You can R or FTR null,
which means you do or do not have evidence for Ha.
M – make your decision (R or FTR)
S – state your conclusion in CONTEXT
P-value shows….
Large-Sample Hypothesis Test for
Population Proportion
A – assumptions
Same as assumptions for confidence interval
T – test statistic
z
p
 (1   )
n

One-Sample t Test for Population
Mean
A – assumptions
Same as assumptions for confidence interval
Sample size must be large OR population approximately normal
T – test statistic
x 
t
s
n
Statistical vs. Practical
Significance
Formula Sheet