Statistics Exam 3: Vocabulary & T/F
k
# of groups
General Notations
All Chapters
Chapter 17
Anova Notations/Vocabulary
Homework 9, Chapter 15 & 17
Chi-Square Test AND Anova Tests
A t curve is bell-shaped like the z curve but is less spread out.
False
For a sample size n, there are n - 1 degrees of freedom associated with the goodness-of-fit test statistic, X^2.
False
If the null hypothesis is not rejected, there is strong statistical evidence that the null hypothesis is true.
False
The P-value for a hypothesis test concerning the difference in two population proportions is always calculated by finding the area to the right of the test statistic, regardless of the alternative hypothesis.
False
The large sample z test for mu1 - mu2 can be used as long as at least one of the two sample sizes, n1 and n2, is greater than or equal to 30.
False
The number of degrees of freedom of the two-sample t test are the same as the degrees of freedom for the paired t test statistic.
False
The power of a test is the probability of failing to reject the null hypothesis.
False
The statistical methods of analysis of an variance assume equal sample means in the null hypothesis
False
α is called the observed significance level.
False (P-Value is OBSERVED significance level)
Homework 6, Chapter 12
One Sample Hypotheses Test for Population Mean
Homework 5: Chapter 10
One Sample Hypotheses Test for Population Proportion
Chapter 10 & 12
One-Sample Hypothesis Testing Vocabulary
Decision
Reject Ho OR Fail to reject Ho
(x bar, subscript 1, minus x bar subscript 2) is an unbiased statistic that is used to estimate mu1 - mu2.
True
A type II error is made by failing to reject a false null hypothesis.
True
An analysis of variance may be used to test the differences in the means of more than two independent populations.
True
As n grows larger, the mean of the sampling distribution of (x bar) gets closer to the population mean.
True
Determining the table value for the F distribution requires two values for degrees of freedom.
True
For n sufficiently large, the distribution of (x bar minus mu, subscript x bar, over sigma subscript x bar) is approximately a standard normal distribution.
True
It is customary to say that the result of a hypothesis test is statistically significant when the P-value is smaller than α.
True
Small P-values indicate that the observed sample is inconsistent with the null hypothesis.
True
The chi-squared test statistic, x^2, measures the extent to which the observed cell count differ from those expected H subscript zero, is true.
True
The hypothesis (P1=P2) is equivalent to the hypothesis (P1-P2=0).
True
The level of significance of a test is the probability of making a type I error, given that the null hypothesis is true
True
The statistical methods of analysis of variance assume that the populations are normally distributed.
True
Two samples are said to be independent when the selection of the individuals in one sample has no bearing on the selection of those in the other sample.
True
Homework 8, Chapter 13
Two Sample Hypotheses Test for Population Mean AND Matched Pairs Test
Homework 7, Chapter 11
Two Sample Hypotheses Test for Population Proportion
Null hypothesis (Ho)
a claim about the population characteristics that is initially assumed to be true
Hypotheses (Ho & Ha)
a statement/question about the population characteristic
z-test statistic
a value that is computed using sample data that us used to determine the p-value associated with the test
Critical Value
a z-score that is found by shading the rejection region specified by the level of significance
P hat, subscript c
combined sample proportion
df, subscript b
degrees of freedom between (k-1)
df, subscript w
degrees of freedom within (N-k)
SSE
error sum of squares
MSE
mean squared error (SSE/N-k)
MSTr
mean sum of squares (SSTr/k-1)
x-double bar
overall mean
N
overall sample size
sigma
population standard deviation
P
proportion (Probability in Chi-Square test)
x bar
sample mean
x-bar, subscript i
sample mean of each group i
P hat
sample proportion (number of successes over sample size)
n
sample size
n, subscript i
sample size of each group i
s
sample standard deviation
s, subscript i
sample standard deviation
s^2
sample variance
F
test statistic - F ratio (MSTr/MSE)
Uo (mu)
the hypothesized value, the value you believe is true for the population mean
Po
the hypothesized value, the value you believe is true for the population proportion
Level of significance (alpha)
the probability of a Type I Error
P-Value
the probability of observing values more extreme than the test statistic
Alternative hypothesis
the research question (dictates how to shade the z-curve)
Type II Error
the researcher failed to reject the null hypothesis, but the null hypothesis was false
Type I Error
the researcher rejected the null hypothesis, but the null hypothesis was true
The spread of the sample mean decreases when
the sample size is increases.
SSTr
treatment sum of squares
Mu (u)
true mean
