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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