ENDTERM Flashcards
The probability distribution of a statistic
Sampling distribution
The statistic of the point estimate
Point Estimator
The difference between the sample measure and the corresponding population measure since the sample is not a perfect representation of the population.
Sampling error
We use statistical inference when we use ___________ methods to make decisions and draw conclusions about ___________.
statical, population
A sample that is chosen at random from a population is important.
Unbiased sample
A method of obtaining the sample by using chance methods in such a way that every member of the population has an equal chance of being selected.
Random Sampling
Number each subject or respondent of the population and select every kth subject.
Systematic Sampling
(k = population size over sample size)
Stratified Sampling
divide the population into groups or strata according to some characteristics that are important to the study. (random selection)
Cluster Sampling
population are divided into sections or clusters.
Multistage Sampling
Combination of basic sampling methods
Some population parameter is a single numeric value ø of a statistic.
Point estimate
Making inferences about parameters where one predicts the value of the population parameter.
parameter estimation
The population is segmented into mutually exclusive subgroups.
Quota Sampling
Sampling units are selected according to the purpose, used for some specific purposes.
Purposive Sampling
Sampling by referal, if finding for participants is difficult
snowball sampling
3 Sample Size Criteria
- Level of Precision
- Confidence Level
- Degree of Variability
Sometimes called as the sampling error. Ranges are expressed in percentage. Ex: (±5%)
Level of precision
Sometimes called as the risk level
Confidence Level
The distribution of the attributes of the population.
Degree of variability
What does census do for a small population?
Eliminates sampling error and provides data of all individuals in the population.
With the assumption that the confidence coefficient is 95% and the population proportion is close to 0.5, we can use the
Slovin’s Formula
Slovin’s Formula
n = N / 1 + Ne²
where N is ths population size and e is the margin of error (0.05)
conjecture about a population parameter. may or may not be true
statistical hypothesis
a statistical hypothesis that states that there is no difference between a parameter and a specific value.
Null Hypothesis (Ho)
statement that the parameter has a value that differs from the null hypothesis
Alternative Hypothesis (H1)
Known as the research hypothesis
AH
Indicates that the null hypothesis should be rejected when the test value is in critical region on one side of the mean.
One tailed tes
Indicates that the null hypothesis should ve rejected when the test value is in either of the two critical regions.
Two-tailed Test
uses the data obtained from a sample to decide whether the null hypothesis should be rejected.
Statistical Test
The numerical value obtained from a statistical test.
Test Value
separates the critical region from the non-critical region.
Critical Value
the range of values of the test statistic that cause us to reject the null hypothesis.
critical or rejection region
Type 1 error
rejecting a true null hypothesis
type II error
failing to reject a false null hypothesis
commonly used confidence level
90, 95, 99%
Central Limit Theorem
when sample size is large, approximately 95% of the samples means taken from the population and the same sample size will fall within 1.96 standard errors of the population mean. μ = 1.96 +-((ó)/√n)
we are testing the population characteristics such as means, variances, and proportions that involve assumptions about the populations from which the sample were selected.
Parametric Test
z, t, and f tests are parametric tests
true
test value formula
(observed value - expected value) / standard error
A statistical test for the mean of the population. Can be used if n > 30 or when the population is normal distributed and ó is known.
z test for a mean
statistical test for the mean o a population.
used whem population is (approximately) normally distributed and ó is unknown.
t test for a mean
When we compare three or more populations, we can use analysis of variance or simply
ANOVA
Who introduced ANOVA?
Ronald A. Fisher
Are conducted after finding significant differences in the analysis of variance.
Post-hoc Tests
test used when testing the difference between two means from dependent samples.
Paired samples t test
Also known as related T test
Period Samples t Test
a statistical method used to determine of there is an existing linear relationship between variables.
Correlation
a statistical measure of the strength of linear relationship between paired data.
Pearson’s correlation coefficient
pioneered research in the area of correlation.
histograms
mode
Karl Pearson
Used if the value of correlation coefficient is significant.
Regression Analysis
the developer of Spearman correlation.
Charles Spearman
Known an distribution-free methods are used to test hypotheses that di not involve specific population parameters.
Nonparametric Methods
Disadvantages of nonparametric tests
less sensitive that parametric counterparts
use less information
less efficient
Positive values denote positive correlation
True. negative values denote negative correlation
sd of each dependent variables must be the same for each value of iv
homoscedasticity
variance is Greater than 1 and the mean, median, mode are equal to zero.
T distribution
T distribution is sometimes called _______ because this was after the pseudonym of W.S. Gosset.
The student t-tes
