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49 Cards in this Set

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SHAPE
YOU DESCRIBE THIS BY TALKING ABOUT THE MODES, THE SKEWNESS, AND THE OUTLIERS (IF ANY)
CENTER
THIS DESCRIBES THE TYPICAL VALUE OF DATA
MEAN
IF YOU HAVE A SYMMETRIC GRAPH, YOU USE ____ TO DESCRIBE THE TYPICAL VALUE OF DATA
MEDIAN
IF YOU HAVE A SKEWED GRAPH, YOU USE ____ TO DESCRIBE THE TYPICAL VALUE OF DATA
UNIMODAL
THERE IS 1 MODE AND A SINGLE PEAK
BIMODAL
THERE ARE 2 MODES AND 2 PEAKS
MULTIMODAL
THERE ARE MORE THAN 2 MODES AND MANY PEAKS
UNIFORM
ROUGHLY FLAT, NO PEAK/SHAPE
STANDARD DEVIATION
IF YOU HAVE A SYMMETRICAL GRAPH, YOU USE THIS (SX OR RANGE/IQR)
RANGE/IQR
IF YOU HAVE A SKEWED GRAPH, YOU USE THIS (SX OR RANGE/IQR)
SKEWED TO THE LEFT
MEDIAN > MEAN
TAIL IS TO THE LEFT
SKEWED TO THE RIGHT
MEDIAN < MEAN
TAIL IS TO THE RIGHT
MEAN, STANDARD DEVIATION
THESE ARE EFFECT BY OUTLIERS SO THEY ARE NOT RESISTANT
MEDIAN, IQR
THESE AREN'T EFFECTED BY OUTLIERS; THESE ARE RESISTANT
OUTLIER TEST
Q3 + 1.5 (IQR)
Q1 - 1.5 (IQR)
INTERQUARTILE RANGE
Q3-Q1
FIVE NUMBER SUMMARY
MIN. Q1 MEDIAN Q3 MAX.
POSITIVE, NEGATIVE, OR NONE
YOU USE THESE TO DESCRIBE DIRECTION
LINEAR, CURVED, OR NONE
YOU USE THESE TO DESCRIBE FORM
STRONG, MODERATE, WEAK
YOU USE THESE TO DESCRIBE STRENGTH
CORRELATION
R VALUE
STRONG .75-1
MEDIUM .6-.75
WEAK .4-.6
CORRELATION OF DETERMINATION
MEASURES FRACTION OF VARIATION IN VALUES OF Y THAT IS EXPLAINED BY LSR ON THE OTHER VARIABLE
LSRL (LEAST SQUARES REGRESSION LINE)
Y=A+BX
RESIDUAL
Y - Y (HAT)

OBSERVED - PREDICTED
RESIDUAL PLOT- NO PATTERN
DATA IS APPROPRIATE
RESIDUAL PLOT - CURVED PATTERN
DATA IS NOT APPROPRIATE (RESIDUAL PLOT)
DESCRIBING SLOPE
FOR EVERY n INCREASE IN y THERE'S AN INCREASE OF 1 IN x
DESCRIBE R2
n% OF VARIATION IN y IS EXPLAINED BY x
NEGATIVE RESIDUAL
WHEN PREDICTED VALUE IS GREATER AND OBSERVED VALUE IS LOWER
FORMULA FOR SLOPE
B=Rsx/sx
INTERCEPT
A = Y-BX
BINOMIAL
HAS FIXED OBSERVATIONS (N) (N,P,X)
GEOMETRIC
OBSERVATIONS AREN'T FIXED (N)
(P, X)
GEOMETRIC/BINOMIAL MEANS
EACH OBSERVATION FALLS INTO 2 CATEGORIES (SUCCESS OR FAILURE)
ALL ARE INDEPENDENT
PROBABILITY OF SUCCESS IS THE SAME
PDF
ASSIGNS PROBABILITY TO EACH VALUE OF X
P(X=N)
CDF
CALCULATES SUM OF PROBABILITIES FOR X
P(X ≧ N)
DENSITY CURVE
A SMOOTH CURVE THAT APPROXIMATES THE SHAPE OF A HISTOGRAM AND DESCRIBES THE PATTERN OF A DISTRIBUTION
PROPERTIES OF A NORMAL DENSITY CURVE
SYMMETRIC
PEAK CENTERED ABOVE MEAN
SPREAD OF CURVE IS PROPORTIONAL TO ITS Sx
THE AREA UNDER A NORMAL CURVE IS ALWAYS 1, REGARDLESS OF THE MEAN AND Sx
METHOD FOR IMPROVING THE ACCURACY OF A SAMPLE
USE LARGER SAMPLE SIZES
THIS IS NOT REQUIRED IN AN EXPERIMENTAL DESIGN
BLOCKING
IF YOU MULTIPLY EACH VALUE IS A DATA SET BY 5, THE Sx WILL...
BE FIVE TIMES AS GREATER
CATEGORICAL VARIABLES
NO NUMBERS INVOLVED IN THESE VARIABLES
QUANTITATIVE VARIABLES
NUMBERS INVOLVED IN THESE VARIABLES
IN REGRESSION, THE RESIDUALS ARE...
THE DIFFERENCE BETWEEN THE OBSERVED RESPONSES AND THE VALUES PREDICTED BY THE REGRESSION LINE
POSITIVE RESIDUAL MEANS...
THE FINAL GRADE IS HIGHER THAN WE WOULD PREDICT WITH THE MODEL
IN A LINEAR REGRESSION MODEL THE SUM OF THE RESIDUALS IS ____
AND IF R2 =O THEN THE REGRESSION LINE IS ____
THE SUM OF RESIDUALS IS ZERO; AND THE REGRESSION LINE IS A HORIZONTAL LINE
PROPERTIES OF STANDARD DEVATION
THE Sx IS THE SQUARE ROOT OF THE VARIANCE
THE Sx IS ZERO ONLY WHEN ALL VALUES ARE THE SAME
THE Sx IS STRONGLY AFFECTED BY OUTLIERS
DISCRETE RANDOM VARIABLE
HAS COUNTABLE NUMBERS OF POSSIBLE VALUES

ASSIGNS NUMERICAL VALUES TO THE OUTCOMES OF A RANDOM PHENOMENON
DENOTED BY A CAPITAL LETTER
CONTINUOUS RANDOM VARIABLE
CAN ASSUME ANY VALUE OVER AN INTERVAL OR INTERVALS