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

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 , 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 , 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 , n1, , 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