User Manual
Page 314
Returns standard deviation of elements in list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns product of a list. If two lists are compared, it returns a list of the smaller or larger of each pair of a list. TI-83 Plus Lists 311 LIST MATH Menu LIST MATH Menu To display the...
Returns standard deviation of elements in list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns product of a list. If two lists are compared, it returns a list of the smaller or larger of each pair of a list. TI-83 Plus Lists 311 LIST MATH Menu LIST MATH Menu To display the...
User Manual
Page 317
To evaluate G 2(N-1) from N=1 to 4: stdDev(, variance( stdDev( returns the standard deviation of the corresponding element in list. Complex lists are not valid. Complex lists are not valid. Each freqlist element counts the number of consecutive occurrences ... elements in list. variance( returns the variance of the corresponding element in list. The default value for freqlist is 1. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314
To evaluate G 2(N-1) from N=1 to 4: stdDev(, variance( stdDev( returns the standard deviation of the corresponding element in list. Complex lists are not valid. Complex lists are not valid. Each freqlist element counts the number of consecutive occurrences ... elements in list. variance( returns the variance of the corresponding element in list. The default value for freqlist is 1. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314
User Manual
Page 368
... x values sum of x values sum of x2 values sample standard deviation of x population standard deviation of x number of data points mean of y values sum of y values sum of y2 values sample standard deviation of y population standard deviation of y sum of x values 1.Var Stats v Gx Gx2... Sx sx n minX 2.Var Stats v Gx Gx2 Sx sx n w Gy Gy2 Sy sy Gxy minX Other VARS menu XY G G XY XY XY XY G G XY XY G XY TI-83 Plus Statistics 365 To access these variables for use in the column below . If you edit...
... x values sum of x values sum of x2 values sample standard deviation of x population standard deviation of x number of data points mean of y values sum of y values sum of y2 values sample standard deviation of y population standard deviation of y sum of x values 1.Var Stats v Gx Gx2... Sx sx n minX 2.Var Stats v Gx Gx2 Sx sx n w Gy Gy2 Sy sy Gxy minX Other VARS menu XY G G XY XY XY XY G G XY XY G XY TI-83 Plus Statistics 365 To access these variables for use in the column below . If you edit...
User Manual
Page 384
... population with an assumed mean of 165.1 centimeters and a standard deviation of 6.35 centimeters (randNorm(165.1,6.35,90) with a seed of 10 Women 169.43 168.33 159.55 169.97 159.79 181.42 171.17 162.04 167.15 159.53 TI-83 Plus Inferential Statistics and Distributions 381 Read the chapter for...
... population with an assumed mean of 165.1 centimeters and a standard deviation of 6.35 centimeters (randNorm(165.1,6.35,90) with a seed of 10 Women 169.43 168.33 159.55 169.97 159.79 181.42 171.17 162.04 167.15 159.53 TI-83 Plus Inferential Statistics and Distributions 381 Read the chapter for...
User Manual
Page 387
... . The bottom line gives the sample size n. Press ... | 8 to select Inpt:Stats. TI-83 Plus Inferential Statistics and Distributions 384 The actual mean þ of 163.8 and sample standard deviation Sx of women's heights, increase the sample size to compute this interval. Use a sample mean...use the Stats (summary statistics) input option. 7. This is between about a 14.2 centimeters spread. The third line gives the sample standard deviation Sx. Interpret the results. The first line, (159.74,173.94), shows that the 99 percent confidence interval for TInterval. To ...
... . The bottom line gives the sample size n. Press ... | 8 to select Inpt:Stats. TI-83 Plus Inferential Statistics and Distributions 384 The actual mean þ of 163.8 and sample standard deviation Sx of women's heights, increase the sample size to compute this interval. Use a sample mean...use the Stats (summary statistics) input option. 7. This is between about a 14.2 centimeters spread. The third line gives the sample standard deviation Sx. Interpret the results. The first line, (159.74,173.94), shows that the 99 percent confidence interval for TInterval. To ...
User Manual
Page 388
8. TI-83 Plus Inferential Statistics and Distributions 385 The results are displayed on the home screen. Press y = to clear the home screen. Press ' to display the DISTR (distributions) ...; 163 Ë 8 Í to store 163.8 to Sx. If the height distribution among a population of women is normally distributed with a mean m of 165.1 centimeters and a standard deviation σ of 6.35 centimeters, what height is exceeded by only 5 percent of the women (the 95th percentile)? 10. Press 7 Ë 1 Í to store 7.1 to ü...
8. TI-83 Plus Inferential Statistics and Distributions 385 The results are displayed on the home screen. Press y = to clear the home screen. Press ' to display the DISTR (distributions) ...; 163 Ë 8 Í to store 163.8 to Sx. If the height distribution among a population of women is normally distributed with a mean m of 165.1 centimeters and a standard deviation σ of 6.35 centimeters, what height is exceeded by only 5 percent of the women (the 95th percentile)? 10. Press 7 Ë 1 Í to store 7.1 to ü...
User Manual
Page 390
14. TI-83 Plus Inferential Statistics and Distributions 387 Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. up is the upper bound. Press Í to paste ShadeNorm( to plot and shade the normal curve. Press Í to the home screen. Area is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. The normal curve is the area above the 95th percentile. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. low is the lower bound.
14. TI-83 Plus Inferential Statistics and Distributions 387 Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. up is the upper bound. Press Í to paste ShadeNorm( to plot and shade the normal curve. Press Í to the home screen. Area is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. The normal curve is the area above the 95th percentile. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. low is the lower bound.
User Manual
Page 399
It tests the null hypothesis H0: m=m0 against one -sample z test; item 1) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is known. Z.Test Z.Test (one of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) In the example: L1={299.4 297.7 301 298.9 300.2 297} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 396
It tests the null hypothesis H0: m=m0 against one -sample z test; item 1) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is known. Z.Test Z.Test (one of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) In the example: L1={299.4 297.7 301 298.9 300.2 297} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 396
User Manual
Page 400
... of 4 (Chapter 1). It tests the null hypothesis H0: m=m0 against one -sample t test; item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown. If you set the decimal mode to Float or a different fixed-decimal setting, your output may differ from the output in the examples...: Data , Stats , Note: All STAT TESTS examples assume a fixed-decimal mode setting of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397
... of 4 (Chapter 1). It tests the null hypothesis H0: m=m0 against one -sample t test; item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown. If you set the decimal mode to Float or a different fixed-decimal setting, your output may differ from the output in the examples...: Data , Stats , Note: All STAT TESTS examples assume a fixed-decimal mode setting of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397
User Manual
Page 402
The null hypothesis H0: m1=m2 is tested against one of two populations (m1 and m2) based on independent samples when both population standard deviations (s1 and s2) are known. item 3) tests the equality of the means of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) In the example: LISTA={154 109 137 115 140} LISTB={108 115 126 92 146} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 399 2.SampZTest 2.SampZTest (two-sample z test;
The null hypothesis H0: m1=m2 is tested against one of two populations (m1 and m2) based on independent samples when both population standard deviations (s1 and s2) are known. item 3) tests the equality of the means of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) In the example: LISTA={154 109 137 115 140} LISTB={108 115 126 92 146} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 399 2.SampZTest 2.SampZTest (two-sample z test;
User Manual
Page 403
The null hypothesis H0: m1=m2 is known. item 4) tests the equality of the means of two populations (m1 and m2) based on independent samples when neither population standard deviation (s1 or s2) is tested against one of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) TI-83 Plus Inferential Statistics and Distributions 400 Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test;
The null hypothesis H0: m1=m2 is known. item 4) tests the equality of the means of two populations (m1 and m2) based on independent samples when neither population standard deviation (s1 or s2) is tested against one of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) TI-83 Plus Inferential Statistics and Distributions 400 Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test;
User Manual
Page 408
In the example: L1={299.4 297.7 301 298.9 300.2 297} Data Stats Input: , , Calculated results: TI-83 Plus Inferential Statistics and Distributions 405 item 7) computes a confidence interval for an unknown population mean m when the population standard deviation s is known. ZInterval ZInterval (one-sample z confidence interval; The computed confidence interval depends on the user-specified confidence level.
In the example: L1={299.4 297.7 301 298.9 300.2 297} Data Stats Input: , , Calculated results: TI-83 Plus Inferential Statistics and Distributions 405 item 7) computes a confidence interval for an unknown population mean m when the population standard deviation s is known. ZInterval ZInterval (one-sample z confidence interval; The computed confidence interval depends on the user-specified confidence level.
User Manual
Page 409
TInterval TInterval (one-sample t confidence interval; item 8) computes a confidence interval for an unknown population mean m when the population standard deviation s is unknown. In the example: L6={1.6 1.7 1.8 1.9} Data Stats Input: , , Calculated results: TI-83 Plus Inferential Statistics and Distributions 406 The computed confidence interval depends on the user-specified confidence level.
TInterval TInterval (one-sample t confidence interval; item 8) computes a confidence interval for an unknown population mean m when the population standard deviation s is unknown. In the example: L6={1.6 1.7 1.8 1.9} Data Stats Input: , , Calculated results: TI-83 Plus Inferential Statistics and Distributions 406 The computed confidence interval depends on the user-specified confidence level.
User Manual
Page 410
In the example: LISTC={154 109 137 115 140} LISTD={108 115 126 92 146} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 407 The computed confidence interval depends on the user-specified confidence level. 2.SampZInt 2.SampZInt (two-sample z confidence interval; item 9) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are known.
In the example: LISTC={154 109 137 115 140} LISTD={108 115 126 92 146} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 407 The computed confidence interval depends on the user-specified confidence level. 2.SampZInt 2.SampZInt (two-sample z confidence interval; item 9) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are known.
User Manual
Page 411
In the example: SAMP1={12.207 16.869 25.05 22.429 8.456 10.589} SAMP2={11.074 9.686 12.064 9.351 8.182 6.642} TI-83 Plus Inferential Statistics and Distributions 408 Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval; The computed confidence interval depends on the userspecified confidence level. item 0) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are unknown.
In the example: SAMP1={12.207 16.869 25.05 22.429 8.456 10.589} SAMP2={11.074 9.686 12.064 9.351 8.182 6.642} TI-83 Plus Inferential Statistics and Distributions 408 Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval; The computed confidence interval depends on the userspecified confidence level. item 0) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are unknown.
User Manual
Page 417
The population means and standard deviations are all unknown. 2.SampÜTest, which uses the ratio of sample variances Sx12/Sx22, tests the null hypothesis H0: s1=s2 against one of the alternatives below. • Ha: s1ƒs2 (s1:ƒs2) • Ha: s1s2) In the example: SAMP4={ SAMP5={ 7 L4 18 17 L3 L5 1 10 11L2} L1 12 L1 L3 3 L5 5 2L11 L1L3} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 414 2.SampÜTest 2.SampÜTest (two-sample Û-test; item D) computes an Û-test to compare two normal population standard deviations (s1 and s2).
The population means and standard deviations are all unknown. 2.SampÜTest, which uses the ratio of sample variances Sx12/Sx22, tests the null hypothesis H0: s1=s2 against one of the alternatives below. • Ha: s1ƒs2 (s1:ƒs2) • Ha: s1s2) In the example: SAMP4={ SAMP5={ 7 L4 18 17 L3 L5 1 10 11L2} L1 12 L1 L3 3 L5 5 2L11 L1L3} Data Stats Input: , , TI-83 Plus Inferential Statistics and Distributions 414 2.SampÜTest 2.SampÜTest (two-sample Û-test; item D) computes an Û-test to compare two normal population standard deviations (s1 and s2).
User Manual
Page 422
... in the same order that you are testing. must be integers | 0. In tests, Draw draws a graph of the population mean , standard deviation, and sample size) for the one-sample tests and intervals. TI-83 Plus Inferential Statistics and Distributions 419 The name of the list containing the data you are testing. The name of output...
... in the same order that you are testing. must be integers | 0. In tests, Draw draws a graph of the population mean , standard deviation, and sample size) for the one-sample tests and intervals. TI-83 Plus Inferential Statistics and Distributions 419 The name of the list containing the data you are testing. The name of output...
User Manual
Page 423
...names of observations in List1 and List2 for the 1.PropZTest and 1.PropZInt. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for sample one for the two-sample tests and intervals. sample tests and intervals. Must be an integer , ...the 1.PropZTest and 1.PropZInt. Must be an integer > 0. Must be a real number > 0. TI-83 Plus Inferential Statistics and Distributions 420 Input Description s2 The known population standard deviation from sample one and sample two in the two- x The count of successes from the second population...
...names of observations in List1 and List2 for the 1.PropZTest and 1.PropZInt. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for sample one for the two-sample tests and intervals. sample tests and intervals. Must be an integer , ...the 1.PropZTest and 1.PropZInt. Must be an integer > 0. Must be a real number > 0. TI-83 Plus Inferential Statistics and Distributions 420 Input Description s2 The known population standard deviation from sample one and sample two in the two- x The count of successes from the second population...
User Manual
Page 425
... degrees of freedom sample mean of x values for sample 1 and sample 2 sample standard deviation of x for sample 1 and sample 2 number of data points for sample 1 and sample 2 pooled standard deviation estimated sample proportion estimated sample proportion for population 1 estimated sample proportion for use in expressions... TEST SxP SxP SxP TEST Ç Ç TEST Ç1 Ç1 TEST Ç2 Ç2 TEST TI-83 Plus Inferential Statistics and Distributions 422 Test and Interval Output Variables The inferential statistics variables are calculated as indicated below .
... degrees of freedom sample mean of x values for sample 1 and sample 2 sample standard deviation of x for sample 1 and sample 2 number of data points for sample 1 and sample 2 pooled standard deviation estimated sample proportion estimated sample proportion for population 1 estimated sample proportion for use in expressions... TEST SxP SxP SxP TEST Ç Ç TEST Ç1 Ç1 TEST Ç2 Ç2 TEST TI-83 Plus Inferential Statistics and Distributions 422 Test and Interval Output Variables The inferential statistics variables are calculated as indicated below .
User Manual
Page 426
TI-83 Plus Inferential Statistics and Distributions 423 Variables confidence interval pair mean of x values sample standard deviation of x number of data points standard error about the line regression/fit coefficients correlation coefficient coefficient of determination regression equation Tests v Sx n LinRegTTest Intervals ANOVA lower, upper v Sx n s a, b r r2 RegEQ VARS Menu TEST XY XY XY TEST EQ EQ EQ EQ Note: The variables listed above cannot be archived.
TI-83 Plus Inferential Statistics and Distributions 423 Variables confidence interval pair mean of x values sample standard deviation of x number of data points standard error about the line regression/fit coefficients correlation coefficient coefficient of determination regression equation Tests v Sx n LinRegTTest Intervals ANOVA lower, upper v Sx n s a, b r r2 RegEQ VARS Menu TEST XY XY XY TEST EQ EQ EQ EQ Note: The variables listed above cannot be archived.