Stats 156 – Calculator Stuff
Stats 156 – Calculator Stuff
Summary of a List of Data
Put the data in L1 inside the STAT “EDIT” menu
Go back to the STAT menu and go over to “CALC
Choose 1-Var Stats
[pic] is the mean
Sx is the standard deviation assuming the data was a sample
(x is the standard deviation assuming the data was the entire population
Q1 is the lower quartile
Q3 is the upper quartile
Med is the median
Standard Normal Distribution
In DISTR
1. normalcdf(a, b) gives the standard normal probability P(a < z < b)
2. invNorm(#) gives the z – value z* such that P(z < z*) = #
General Normal Distribution
In DISTR
1. normalcdf(a, b, (, () gives the probability P(a < x < b)
where x has normal distribution with mean = ( and standard deviation = (
2. invNorm(#, (, () gives the x –value x* such that P(x < x*) = #
where x has normal distribution with mean = ( and standard deviation = (
Confidence Interval for (
In STAT – inside TESTS
1. 1-PropZInt
x = # successes, n = sample size, C – Level = desired confidence level
Confidence Interval for (
In STAT – inside TESTS
1. ZInterval (if ( is known) or
2. TInterval (if ( is unknown)
Choose “Data” if data is in L1
Choose “Stats” if [pic], n, and standard deviation (population or sample) is known
One Sample z Test for a Population Proportion
In STAT – inside TESTS
1. 1-PropZTest
p0 = hypothesized value of proportion
x = number of successes
n = sample size
One Sample t Test (or z Test) for a Population Mean
In STAT – inside TESTS
1. Z-Test… (if ( is known) or
2. T-Test… (if ( is unknown)
Choose “Data” if data is in L1
Choose “Stats” if [pic], n, and standard deviation (population or sample) are known
Two Sample t Test for Difference in 2 Population Means
In STAT – inside TESTS
1. 2-SampZTest…(if ( is known) or
2. 2-SampTTest…(if ( is unknown)
Choose “Data” if data is in L1
Choose “Stats” if [pic], n1, [pic], n2, and standard deviations (populations or samples) are
known
Two Sample z Test for Difference in 2 Population Proportions
In STAT – inside TESTS
1. 2PropZTest
x1 = number of successes in sample 1
n1= sample 1 size
x2= number of successes in sample 2
n2= sample 2 size
χ2 Goodness of Fit Test
1. Put observed counts in L1 and hypothesized π’s in L2
Go to PRGM
Choose CHI2
χ2 Test of Independence/Association
1. Put the table into a matrix in the calculator
• Go to MATRIX in the calculator
• Choose “EDIT” and 1:[A]
• Enter the size of the matrix (number of rows by number of columns)
• Enter data in the matrix
2. Run χ2 test in calculator (not the program)
• Press STAT and choose “TESTS”
• Choose χ2–Test
Single Factor ANOVA – F-Test
1. From Raw Data
• Put the data for each sample in lists L1, L2, …
• Press STAT and choose “TESTS”
• Choose ANOVA(
• Enter ANOVA(L1, L2, …)
2. From Summary Statistics
• Enter the sample sizes in L1
• Enter the sample means in L2
• Enter the sample standard deviations in L3
• Press PRGM and choose ANOVA1
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