F R E Q U E N T LY U S E D F O R M U L A S n = sample size
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N = population size
Chapter 2
f = frequency
Chapter 5
Class width =
high - low (increase to next integer) number of classes
Class midpoint =
Probability of the complement P(Ac) = 1 - P(A)
Multiplication rule for indepen P(A and B) = P(A) # P(B)
upper limit + lower limit 2
Lower boundary = lower boundary of previous class + class width
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General multiplication rules P(A and B) = P(A) # P(B!A P(A and B) = P(B) # P(A!B
Addition rule for mutually exc Chapter 3 3$%!"#$%&'#()$*"&'($'#+'#,#-(,$("#$.)//)01-2$&*(131(1#,$*&4,1-2$5#&("6$("#$-478#'$).$+#)+/#$ P(A or B) = P(A) + P(B) 0")$51#5$1-$&$*&/#-5&'$9#&'$0"1/#$)-$&$*)77#'*1&/$./12"(:$;<=$1-$("#$8&("(48:$;>?=$89$ ©x Sample mean x = General addition rule +)1,)-1-2:$@@A<=$&,$+#5#,('1&-,:$B;?C=$74'5#'#5$89$,+)4,#,:$BB@D=$.')7$.&//,:$<>D?=$1-$ n P(A or B) = P(A) + P(B) 7)()'$3#"1*/#$&**15#-(,:$A?<<DE$F"&($1,$("#$3&/4#$.)'$G#HI$ ©x Population mean m = n! N Permutation rule Pn,r = (n - r ©xw Weighted average = n ©w Combination rule Cn,r = r!(n Range = largest data value - smallest data value 2
Sample standard deviation s =
©(x - x) B n - 1 2
Computation formula s =
2
©x - (©x) !n n - 1 B
©(x - m)2 Population standard deviation s = N B Sample variance s2
Chapter 6
Mean of a discrete probability
Standard deviation of a discret s = 2©(x - m)2P(x)
For Binomial Distributions
r = number of successes; p = q = 1 - p
Binomial probability distributi % % Population variance s2 % Mean m = np % s# % Standard deviation s = 2npq 100 Sample coefficient of variation CV = $ x >E$J$,4'3#9$).$A???$&54/(,$4-*)3#'#5$,)7#$1-(#'#,(1-2$")4,#K##+1-2$,#*'#(,E$F"#-$ Chapter 7 ©xf Sample mean for grouped data x = 4-#L+#*(#5$*)7+&-9$*)7#,:$0"#'#$5)$0#$"15#$("#$7#,,I$!"#$,4'3#9$,")0#5$("&($<@M$ n Raw score x = zs + m ).$("#$'#,+)-5#-(,$(),,$("#1'$7#,,$1-$("#$*/),#(:$ANM$,")3#$("1-2,$4-5#'$("#$8#5:$<M$+4($ Sample standard deviation for grouped data ("1-2,$1-$("#$8&("(48:$&-5$NM$+4($("#$7#,,$1-$("#$.'##O#'E$P&K#$&$*1'*/#$2'&+"$()$51,+/&9$ 2 Mean of x distribution mx = m ©x2f - (©xf )2!n ("1,$1-.)'7&(1)-E$©(x - x) f s = = n - 1 B n - 1 B Q)0$7&-9$5#2'##,$G()$)-#$5#*17&/$+/&*#H$'#+'#,#-($("#$-478#'$).$+#)+/#$0")$"15#$ Standard deviation of x distrib ("#1'$7#,,$1-$("#$8&("(48I$ Chapter 4 $ x x z = Standard score for ; $ Regression and Correlation s! Pearson product moment correlation coefficient
Chapter 8
r =
n©xy - (©x)(©y) 2
2
2
Confidence Interval 2
2n©x - (©x) 2n©y - (©y)
for m
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