User Manual
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...( 6:prod( 7:stdDev( 8:variance( Returns minimum element of a list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns standard deviation of elements in listA and listB. TI-83 Plus Lists 311 If two lists are compared, it returns a list of the smaller or larger of each pair of a list. NAMES OPS...
...( 6:prod( 7:stdDev( 8:variance( Returns minimum element of a list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns standard deviation of elements in listA and listB. TI-83 Plus Lists 311 If two lists are compared, it returns a list of the smaller or larger of each pair of a list. NAMES OPS...
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variance( returns the variance of the corresponding element in list. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314 Each freqlist element counts the number of consecutive occurrences of the elements in list. Complex lists are not valid. The default value for ... not valid. Each freqlist element counts the number of consecutive occurrences of the elements in list. To evaluate G 2(N-1) from N=1 to 4: stdDev(, variance( stdDev( returns the standard deviation of the corresponding element in list. The default value for freqlist is 1.
variance( returns the variance of the corresponding element in list. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314 Each freqlist element counts the number of consecutive occurrences of the elements in list. Complex lists are not valid. The default value for ... not valid. Each freqlist element counts the number of consecutive occurrences of the elements in list. To evaluate G 2(N-1) from N=1 to 4: stdDev(, variance( stdDev( returns the standard deviation of the corresponding element in list. The default value for freqlist is 1.
User Manual
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...of 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...
...of 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
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....53 TI-83 Plus Inferential Statistics and Distributions 381 Read the chapter for details. Height (in centimeters) of Each of a Population Getting Started is a fast-paced introduction. The 10 height values below . Suppose you want to be normally distributed, a t distribution confidence interval can be used when estimating the mean of 165.1 centimeters and a standard deviation...
....53 TI-83 Plus Inferential Statistics and Distributions 381 Read the chapter for details. Height (in centimeters) of Each of a Population Getting Started is a fast-paced introduction. The 10 height values below . Suppose you want to be normally distributed, a t distribution confidence interval can be used when estimating the mean of 165.1 centimeters and a standard deviation...
User Manual
Page 387
... sample standard deviation Sx of the population sampled is 165.1 centimeters, which is in a very large number of samples, we expect 99 percent of the intervals calculated to select Inpt:Stats. The actual mean m of the sample þ used to compute this interval. The bottom line gives the sample size n. TI-83 Plus Inferential Statistics... the Stats (summary statistics) input option. 7. The .99 confidence level indicates that you can enter summary statistics as input. The third line gives the sample standard deviation Sx. Press ... | 8 to 90.
... sample standard deviation Sx of the population sampled is 165.1 centimeters, which is in a very large number of samples, we expect 99 percent of the intervals calculated to select Inpt:Stats. The actual mean m of the sample þ used to compute this interval. The bottom line gives the sample size n. TI-83 Plus Inferential Statistics... the Stats (summary statistics) input option. 7. The .99 confidence level indicates that you can enter summary statistics as input. The third line gives the sample standard deviation Sx. Press ... | 8 to 90.
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... 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. The results are displayed on the home screen. TI-83 Plus Inferential Statistics and Distributions 385 Press 7 Ë 1 Í to store 7.1 to calculate...
... 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. The results are displayed on the home screen. TI-83 Plus Inferential Statistics and Distributions 385 Press 7 Ë 1 Í to store 7.1 to calculate...
User Manual
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up is the upper bound. TI-83 Plus Inferential Statistics and Distributions 387 14. Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. Area is the lower bound. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. low is the area above the 95th percentile. The normal curve is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. Press Í to the home screen. Press Í to paste ShadeNorm( to plot and shade the normal curve.
up is the upper bound. TI-83 Plus Inferential Statistics and Distributions 387 14. Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. Area is the lower bound. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. low is the area above the 95th percentile. The normal curve is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. Press Í to the home screen. Press Í to paste ShadeNorm( to plot and shade the normal curve.
User Manual
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item 1) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is known. It tests the null hypothesis H0: m=m0 against one -sample z test; 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
item 1) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is known. It tests the null hypothesis H0: m=m0 against one -sample z test; 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
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...; Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397 If you set the decimal mode to Float or a different fixed-decimal setting, your output may differ from the output in the examples. item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown.
...; Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397 If you set the decimal mode to Float or a different fixed-decimal setting, your output may differ from the output in the examples. item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown.
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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;
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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
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The computed confidence interval depends on the user-specified confidence level. ZInterval ZInterval (one-sample z confidence interval; item 7) computes a confidence interval for an unknown population mean m when the population standard deviation s is known. 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
The computed confidence interval depends on the user-specified confidence level. ZInterval ZInterval (one-sample z confidence interval; item 7) computes a confidence interval for an unknown population mean m when the population standard deviation s is known. 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
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TInterval TInterval (one-sample t confidence interval; 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 item 8) computes a confidence interval for an unknown population mean m when the population standard deviation s is unknown. The computed confidence interval depends on the user-specified confidence level.
TInterval TInterval (one-sample t confidence interval; 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 item 8) computes a confidence interval for an unknown population mean m when the population standard deviation s is unknown. The computed confidence interval depends on the user-specified confidence level.
User Manual
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item 9) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are known. 2.SampZInt 2.SampZInt (two-sample z confidence interval; 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.
item 9) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are known. 2.SampZInt 2.SampZInt (two-sample z confidence interval; 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.
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Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval; 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 item 0) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are unknown. The computed confidence interval depends on the userspecified confidence level.
Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval; 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 item 0) computes a confidence interval for the difference between two population means (m1Nm2) when both population standard deviations (s1 and s2) are unknown. The computed confidence interval depends on the userspecified confidence level.
User Manual
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2.SampÜTest 2.SampÜTest (two-sample Û-test; 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 item D) computes an Û-test to compare two normal population standard deviations (s1 and s2).
2.SampÜTest 2.SampÜTest (two-sample Û-test; 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 item D) computes an Û-test to compare two normal population standard deviations (s1 and s2).
User Manual
Page 422
... the one-sample tests and intervals. The known population standard deviation from the first population for tests and intervals. The known population standard deviation; The name of the population mean , standard deviation, and sample size) for the data in List. ...Summary statistics (mean that they appear in this chapter. must be a real number > 0. Default=1. In tests, Draw draws a graph of the list containing the data you are testing. TI-83 Plus...
... the one-sample tests and intervals. The known population standard deviation from the first population for tests and intervals. The known population standard deviation; The name of the population mean , standard deviation, and sample size) for the data in List. ...Summary statistics (mean that they appear in this chapter. must be a real number > 0. Default=1. In tests, Draw draws a graph of the list containing the data you are testing. TI-83 Plus...
User Manual
Page 423
Must be an integer , 0. p0 The expected sample proportion for the two-sample tests and intervals. TI-83 Plus Inferential Statistics and Distributions 420 Defaults=1. Must be a real number > 0. Freq1, Freq2 The names of the lists containing the frequencies...sample for the 2.PropZTest and 2.PropZInt. No instructs the TI.83 not to pool the variances. Yes instructs the TI.83 to pool the variances. Defaults are testing for 2.SampTTest and 2.SampTInt. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for sample one for the ...
Must be an integer , 0. p0 The expected sample proportion for the two-sample tests and intervals. TI-83 Plus Inferential Statistics and Distributions 420 Defaults=1. Must be a real number > 0. Freq1, Freq2 The names of the lists containing the frequencies...sample for the 2.PropZTest and 2.PropZInt. No instructs the TI.83 not to pool the variances. Yes instructs the TI.83 to pool the variances. Defaults are testing for 2.SampTTest and 2.SampTInt. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for sample one for the ...
User Manual
Page 425
...199; TEST Ç1 Ç1 TEST Ç2 Ç2 TEST TI-83 Plus Inferential Statistics and Distributions 422 Variables p-value test statistics 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...
...199; TEST Ç1 Ç1 TEST Ç2 Ç2 TEST TI-83 Plus Inferential Statistics and Distributions 422 Variables p-value test statistics 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...
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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. TI-83 Plus Inferential Statistics and Distributions 423