Statistics flashcards, diagrams and study guides
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Attempt to contact every individual in the entire population.
A specific experimental condition applied to the units/subjects
Systematically favors certain outcomes
the mean of the population is equal to 55 the population proportion is not less than .65
the mean of the population is greater than 55 the population proportion is less than .65
you don't reject a null hypothesis that is false
Descriptive statistics determined from a sample are used to estimate parameters of the population. This is possible when all individuals in the population have an equal chance of being sampled and individuals are sampled independently.
To answer this question, we need to know something about how the sampling process might effect the estimates we make, using the sampling distribution of the estimate.
the probability distribution of all values for an estimate that we might obtain when we sample a population
. The null hypothesis would say that class size has no effect on student learning.
2. False. A larger alpha means that the boundaries for the critical region move closer to the center of the distribution.
3. The .02 would be split between the two tails, with .01 in each tail. The z-score boundaries would be z = +2.33 and z = —2.33
The null hypothesis, denoted by H0, is usually the hypothesis that sample observations result purely from chance.
The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some non-random cause.
A Type I error occurs when the researcher rejects a null hypothesis when it is true. The probability of committing a Type I error is called the significance level. This probability is also called alpha, and is often denoted by α.
d. Do not reject Ho at all common levels of alpha
d. A statement that will be accepted only if there is convincing sample evidence that it is true
c. reject Ho if alpha is 0.05
A CHARACTERISTIC THAT CHANGES FROM PERSON TO PERSON, ATTRIBUTES ABOUT INDIVIDUALS VARY FROM PERSON TO PERSON. WE EXAMINE VARIABLES TO DETERMINE WHETHER THEY ARE RELATED TO ONE ANOTHER OR NOT. EG. GENDER - INCOME LEVEL - ATTITUDE ABOUT SEX EDUCATION IN PUBLIC SCHOOLS
THE LEVELS OF MEASUREMENT INCLUDE THE FOLLOWING: - NOMINAL - ORDINAL - CONTINUOUS
THE LEVEL OF MEASUREMENT IS IMPORTANT TO RECOGNIZE IN ORDER TO DETERMINE WHAT KIND OF STATISTICAL TEST TO PERFORM
A chart representing data that shows the frequency that a statistic occurs on a number line, usually represented with marks above the number line for every occurrence of a simulation or data point occurring.
Experimentally determine the outcome of a study, through manipulation of objects or using an online applet.
Represents the probability or the percentage likelihood of an event occurring through random chance.
An inferential statistical method that uses the data from a sample to draw inferences about a population
The actual distance between a sample mean M and a population mean µ.
The average distance between a sample mean M and the population mean µ that would be expected if H0 was true.
The objects described by a set of data
The midpoint of a distribution of quantitative data
A _________ distribution describes the distribution of values of a categorical variable among individuals who have a specific value of another variable
b) consumers, evaluators, and creators of science
e) All of the above
100 research studies, 61 not replicable, 15% generated completely different results Message of study: research methods are not static, but dynamic.
the arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores
A measure of variability that indicates the average difference between the scores and their mean.
the standard deviation of the sampling distribution of sample means
Q: What is the probability if you pick a sample (say, of 4 people) at random from the population, that this sample's mean will be greater than 132? Before: p( x > 132 ) Now: p ( x̅ > 132 ) So, instead of the x guy, we're talking about the . . . x-men.
A: Instead of 1 person at a time, do 1 sample at a time. Sample 1 (4 students): x̅ = 110 Sample 2 (4 students): x̅ = 105 . . . . . . . . . .
A: Still bell-shaped and symmetric BUT . . . • Taller • Thinner Q: How much thinner? A: If the x distribution's sd were σ, then x̅. EX: σ/√N *NOTE: The new graph is called the "sampling distribution of means" (see pg. 170). p( x̅ > 132) = .003% OLD: z = x - μ / σ σ = 16, μ = 100, N = 4 *NEW: z = x̅ - μ / σ/√N Steps: 1) Draw picture 2) x → z 3) go to z table for %