stat flashcards
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| Sample | show 🗑
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| show | Process of selecting sample from population
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| Random sampling | show 🗑
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| show | – Descriptive: primary purpose is to describe some aspect of the data
Inferential: primary purpose is to infer (to estimate or to make a decision, test a hypothesis)
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| show | – use of some descriptive statistic
– use of probability
– potential for estimation
– sampling variability
– sampling distributions
– use of a theoretical distribution
– two hypotheses, two decisions, two types of error
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| Research defined | show 🗑
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| show | – 1. encounter and identify problem
– 2. formulate hypotheses, define variables
– 3. think through consequences of hypotheses
– 4. design & run study, collect data, compute statistics, test hypotheses
– 5. draw conclusions
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| Variable | show 🗑
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| show | its values are manipulated by the researcher, comes first in time
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| show | measured by researcher, follows the IV in time
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| Population | show 🗑
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| show | controlled by researcher
• randomization of subjects to groups
• keep all subjects constant on EV
• include EV in the design of the experiment
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| show | comes first in time but there is no manipulation, analogous to IV.
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| show | follows PV in time, analogous to DV.
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| show | IV causes the DV
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| show | PV predicts the CV
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| 2 Types of research | show 🗑
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| show | • manipulation of IV
• randomization of subjects to groups
• causal relationship between IV and DV
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| Observational research | show 🗑
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| Stem and Leaf Display | show 🗑
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| Description With Statistics Aspects or characteristics of data that we can describe are: | show 🗑
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| show | central tendency, location, center
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| Statistics that Measure middle are: | show 🗑
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| Other words that describe Spread | show 🗑
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| Statistics that Measure spread are: | show 🗑
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| Skewness | show 🗑
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| show | peakedness relative to normal curve
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| Sample Mean | show 🗑
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| Sample Median | show 🗑
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| show | • The mode is the most frequent score.
• Examples:
– 1 1 4 7, the mode is 1.
– 1 1 4 7 7, there are two modes, 1 and 7.
– 1 4 7, there is no mode.
• Characteristics:
– Has problems: more than one, or none; maybe not in the mid
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| Spred cont. | show 🗑
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| show | • Formula is MR=UH-LH
– UH=upper hinge
– LH=lower hinge
– Hinges cut off 25% of the data in each tail
• Hinge position is ([median position]+1)/2.
– [median position] is the whole number part of the median position (remember, median p
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| Hinge position | show 🗑
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| show | • Definitional formula: s*²=S(X-X)²/N, the average squared deviation from X-bar.
Sample Standard Deviation= s*
Unbiased Variance Estimate, s²
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| show | • A pictorial description that uses a box to show the middle of the data and lines called whiskers to show the tails of a distribution.
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| show | 1.) Box
2.) Wiskers
3.) Outliers
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| show | – Upper end is at the UH, lower end is at the LH - Line across the middle is X50
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| Whiskers | show 🗑
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| show | Outliers: outside whiskers, marked with
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| show | UH- LH
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| z Scores | show 🗑
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| show | z is something minus its mean divided by its standard deviation.
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| z score characteristics | show 🗑
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| show | – Symmetric, continuous, unimodal.
– Bell-shaped.
– Scores range from -¥ to +¥ .
– Mean, median, and mode are all the same value.
– Each distribution has two parameters, m and s².
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| Use of Z score | show 🗑
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| Correlation | show 🗑
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| Regression | show 🗑
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| r= | show 🗑
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| r2= | show 🗑
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| Correlation: Undefined | show 🗑
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| show | r (rho)
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| regression cont. | show 🗑
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| show | The statistics b and a are computed so as to minimize the sum of squared errors, – Se2=S(Y-Y’)2 is a minimum. – This is called the Least Squares Criterion.
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| show | – Total = Explained + Not Explained
– This is true for proportion of spread and amount of spread.
• Proportion: 1 = r2 + (1-r2)
• Amount: s2y = s2y r2 + s2y(1-r2)
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| show | Defined as relative frequency of occurence.
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| show | all possible outcomes of an experiment
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| Elementary event | show 🗑
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| Event | show 🗑
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| p(elementary event | show 🗑
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| p(event) | show 🗑
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| Conditional probability | show 🗑
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| show | 1. independence 2. mulitplication, mutually exclusive 3.) addition
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| show | events A and B are independent if
• p(A|B)=p(A)
• The A probability is not changed by
reducing the sample space to B.
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| show | • p(A and B)=p(A)p(B|A)=p(A|B)p(B)
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| show | • Events A and B do not have any elementary events in common.
• Events A and B cannot occur simultaneously.
• p(A and B)=0
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| Addition (Or) Rule (3) | show 🗑
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| The sampling distribution of X-bar | show 🗑
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| Hypothesis testing | show 🗑
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| Test statistic | show 🗑
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| show | conditions placed on a test statistic necessary for its valid use in hypothesis testing;– for zX, the assumptions are that the population is normal in shape and that the observations are independent.
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| show | the hypothesis that we test; Ho.
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| Alternative hypothesis | show 🗑
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| show | he standard for what we mean by a “small” probability in hypothesis testing; a.
The significance level is the small probability used in hypothesis testing to determine an unusual event that leads you to reject Ho.
– The significance level is sym
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| show | >,<, or =
• Directional hypotheses specify a particular direction for values of the parameter.
– IQ of deaf children example: Ho: m>100, H1: m<100.
• Non-directional hypotheses do not specify a particular direction for values of the paramet
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| show | – A one-tailed test is a statistical test that uses only one tail of the sampling distribution of the test statistic.
– A two-tailed test is a statistical test that uses two tails of the sampling distribution of the test statistic.
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| Critical values | show 🗑
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| show | the values of the test statistic that lead to rejection of Ho
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| show | • Reject Ho if
– ½ the SAS p-value <a, and
– the observed zX is in the tail specified by H1.
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