CH 8 & 9 Review
Type 1 Error
A type 1 error occurs when true null hypothesis is rejected. The value of Alpha represents the probability of committing this type of error. The value of Alpha represents the significance level of the test
Type 2 Error
A type 2 error occurs when a false null hypothesis is not rejected. The value of beta represents the probability of committing a type 2 error: B=P times H0 is not rejected | H0 is false, The value of 1- Beta is called the power of test. It represents the probability of not making a type 2 error.
Alternative Hypothesis
Alternative hypothesis is A claim about a population parameter that will be true if the null hypothesis is false.
Confidence Level
Confidence level, denoted by 1 minus alpha times 100%, that states how much confidence we have, that a confidence interval contains the true population parameter.
Degrees of Freedom
Degrees of freedom are The number of observations that can be chosen freely. For estimation of U, using t distribution, the degrees of freedom are n minus 1
Descriptive statistics
Descriptive statistics consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures.
Alpha is less than P
Do not reject
Do not, fail to, reject
Do not reject is the Center of the bell curve
Tails of a test if equal or not equal too:
Equal or not equal than its two tailed
H0 is
H0 is null hypothesis
H1 is
H1 is alternative hypothesis
Tails of a test if greater > than:
If tail is greater than >, then right tailed
Tails of a test if less < than:
If tail is less than < , then left tailed
Inferential statistics
Inferential statistics, Consists of methods that use sample results to help make desisions or predictions about a population.
Interval Estimate
Interval estimate is An interval constructed around the point estimate, that is likely to contain the corresponding population parameter. Each interval estimate has a confidence level.
Level of Significance
Level of significance is The value of alpha that gives the probability of committing a type 1 error
Margin of Error
Margin of error is The quantity that is subtracted from and added to the value of a sample statistic, to obtain a confidence interval for the corresponding population parameter.
Null Hypothesis
Null hypothesis is A claim about a population parameter, that is assumed to be true until proven otherwise.
P-Value
P-value is The smallest significance level at which a null hypothesis can be rejected
Point Estimate
Point estimate is The value of a sample statistic assigned to the corresponding population parameter.
Alpha is greater than P
Reject
Reject
Rejection region in each tail
T is used when
T is used when the population mean is not known
If H0 is equal or greater than > or equal and H1 is less < than:
Than its a left tail test
If H0 is equal to or less than and equal too and H1 is greater than:
Than its a right tail test
If H0 is equal and H1 is not equal too:
Than its a two tailed test
Type 1 Error
Type 1 error is An error that occurs when a true null hypothesis is rejected
Type 2 Error
Type 2 error is An error that occurs when a false null hypothesis is not rejected
Z is used when
Z is used when the population mean is known
Z value for 90% confidence level
Z value for 90% confidence level is 1.65
Z value for 95% confidence level
Z value for 95% confidence level is 1.96
Z value for 99% confidence level
Z value for 99% confidence level is 2.58