Class Table

TI83-84 STATISTICS and DISTRIBUTION Menus



Table of Contents for CALCULATORing
 
Edit   Calculate   Tests
 
Distribution     Diagnostic On     Distribution Draw


EDIT
1:Edit...
2:SortA(
3:SortD(
4:ClrList
5:SetUpEditor


CALCULATE
1:1-Var Stats
2:2-Var Stats
3:Med-Med
4:LinReg(ax+b)
5:QuadReg
6:CubicReg
7:QuadReg
8:LinReg(a+bx)
9:LnReg
A:PwrReg
B:Logistic
C:SinReg
D:Manual-Fit

Click on image to enlarge.


TESTS   On 1 page of notes.
For using data in calculator.
Here for a 2-tail test.

      For using data not in calculator.
Here for a 1-tail test.

    For the test on the right, the following results are returned for [CALCULATE] and [DRAW].

      The user must know the statistics to complete the problem. The calculator will just do the computation.

      See problem 2, A normally distributed standardized math test is known to have a mean of 70% and a standard deviation of 12%. The test is given to 36 freshmen and the class average is 75%. With 99% confidence, complete a hypothesis test to see if the population average is greater than 70%.


1:Z-Test...
      significance test for a mean, sigma known
2:T-Test...
      significance test for a mean, sigma unknown
3:2-SampleZ-Test...
4:2-SampleT-Test...
5:1-PropZ-Test...
      significance test for a proportion
6:2-PropZ-Test...
      significance test for the difference of two proportions
7:Z-Interval...
      confidence interval for a mean,known
8:TInterval...
      confidence interval for a mean,unknown
9:2-SampZInt...
      significance test for the difference of two means, sigma1 and sigma2 known
0:2-SampTInt...
      significance test for the difference of two means, sigma1 and sigma2 unknown
A:1-ProfZInt...
      confidence interval for a proportion
B:2-ProfZInt...
      confidence interval for the difference of two proportions
C:2-Test...
      2 test of homogeneity or independence (not goodness-of-fit)
D:2GOF-Test...
      2-Test
E:2-SampFTest...
F:LinRegTTest...
      significance test for a slope
G:LinRegTInt...
H:ANOVA(


DISTRIBUTION
1:normalpdf(x[,mean,standard deviation])
      normal probability density function
2:normalcdf(lower bound,upper bound[,mean, standard deviation])
      normal cumulative distribution function (area under the curve)
3:invNorm(area[,mean,standard deviation])
      normal distributionís x-value or z-score corresponding to a known area
4:invT(area, degrees of freedom inverse cumulative student-t probability
5:tpdf(x, degrees of freedom) probability density function
      t probability density function
6:tcdf(lower bound, upperbound, degrees of freedom)
      t cumulative distribution function (area under the curve)
7:2pdf(x,degrees of freedom)
      2 probability density function
8:2cdf(lower bound,upperbound,degrees of freedom)
      2cumulative distribution function (area under the curve)
9:Fpdf(x,numerator df,denominator degrees of f)
0:Fcdf(lowerbound,upperbound,numerator df,denominator df)
      F distribution probability between upper and lower bound
A:binompdf(number of trials,probability[,successes])
      binomial probability
B:binomcdf(number of trials,probability[,successes])
      binomial cumulative probability
C:poissonpdf(mean,x) probability at x for the Poisson distribution
D:poissoncdf(mean,x) cumulative Poisson probability at x
E:geometpdf(probability,trial of first success)
      geometric probability
F:geometcdf(probability,trial of first success) geometric cumulative probability


DISTRIBUTION   DRAW
1:ShadeNorm(lowerbound,upperbound[,m,s])
      shades normal curve between lowerbound and upperbound.
2:Shade_t(lowerbound,upperbound,df)
      shades Student-t distribution
3:Shade2(lowerbound,upperbound,df)
      shades 2 between lowerbound and upperbound.
4:ShadeF(lowerbound,upperbound,numer df,denom df)
      shades F curve between lowerbound and upperbound.


DIAGNOSTIC ON
In CATALOG toggle DiagnosticOn or DiagnosticOff
to display
      r (correlation coefficient) and
      r^2 (coefficient of determination)
      R^2 (coefficient of determination).


 
 
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