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Returns product of a list. TI-83 Plus Lists 311 LIST MATH Menu LIST MATH Menu To display the LIST MATH menu, press y 9 |. NAMES OPS MATH 1:min( 2:max( 3:mean of elements in listA ... or largest magnitude (modulus) is returned. Returns mean ( 4:median( 5:sum( 6:prod( 7:stdDev( 8:variance( Returns minimum element of elements in list. Returns sum of a list. Returns standard deviation of elements in a list.
Returns product of a list. TI-83 Plus Lists 311 LIST MATH Menu LIST MATH Menu To display the LIST MATH menu, press y 9 |. NAMES OPS MATH 1:min( 2:max( 3:mean of elements in listA ... or largest magnitude (modulus) is returned. Returns mean ( 4:median( 5:sum( 6:prod( 7:stdDev( 8:variance( Returns minimum element of elements in list. Returns sum of a list. Returns standard deviation of elements in a list.
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Each freqlist element counts the number of consecutive occurrences of the elements in list. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314 The default value for freqlist is 1. Complex lists are not valid. variance( returns the variance of the corresponding element in list. Each freqlist...the number of consecutive occurrences of the elements in list. The default value for freqlist is 1. 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.
Each freqlist element counts the number of consecutive occurrences of the elements in list. stdDev(list[,freqlist]) variance(list[,freqlist]) TI-83 Plus Lists 314 The default value for freqlist is 1. Complex lists are not valid. variance( returns the variance of the corresponding element in list. Each freqlist...the number of consecutive occurrences of the elements in list. The default value for freqlist is 1. 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.
User Manual
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... values sum of y values sum of y2 values sample standard deviation of y population standard deviation of y sum of analysis, all statistical variables are calculated and stored as indicated below under VARS menu. To access these variables for use in the column below . If you edit a list or change the type of x ... y minimum... 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 Then select...
... values sum of y values sum of y2 values sample standard deviation of y population standard deviation of y sum of analysis, all statistical variables are calculated and stored as indicated below under VARS menu. To access these variables for use in the column below . If you edit a list or change the type of x ... y minimum... 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 Then select...
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... 167.15 159.53 TI-83 Plus Inferential Statistics and Distributions 381 The 10 height values below are the first 10 of women given the random sample 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 of 6.35 centimeters (randNorm...
... 167.15 159.53 TI-83 Plus Inferential Statistics and Distributions 381 The 10 height values below are the first 10 of women given the random sample 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 of 6.35 centimeters (randNorm...
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... the sample size n. This is between about a 14.2 centimeters spread. The editor changes so that the 99 percent confidence interval for TInterval. TI-83 Plus Inferential Statistics and Distributions 384 The third line gives the sample standard deviation Sx. The first line, (159.74,173.94), shows that you can enter summary statistics as input.
... the sample size n. This is between about a 14.2 centimeters spread. The editor changes so that the 99 percent confidence interval for TInterval. TI-83 Plus Inferential Statistics and Distributions 384 The third line gives the sample standard deviation Sx. The first line, (159.74,173.94), shows that you can enter summary statistics as input.
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... 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 † 163 Ë 8 Í to store 163.8 to n. 9. TI-83 Plus Inferential Statistics and Distributions 385 Press 90 Í to store 90 to...
... 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 † 163 Ë 8 Í to store 163.8 to n. 9. TI-83 Plus Inferential Statistics and Distributions 385 Press 90 Í to store 90 to...
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low is the area above the 95th percentile. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. Area is the lower bound. up is the upper bound. Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. Press Í to the home screen. 14. Press Í to paste ShadeNorm( to plot and shade the normal curve. The normal curve is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. TI-83 Plus Inferential Statistics and Distributions 387
low is the area above the 95th percentile. Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. Area is the lower bound. up is the upper bound. Ans (175.5448205 from step 11) is the lower bound. 1å99 is the upper bound. Press Í to the home screen. 14. Press Í to paste ShadeNorm( to plot and shade the normal curve. The normal curve is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. TI-83 Plus Inferential Statistics and Distributions 387
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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. 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 It tests the null hypothesis H0: m=m0 against one -sample z test;
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...-decimal mode setting of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397 item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown. It tests the null hypothesis H0: m=m0 against one -sample t test; If you set the...
...-decimal mode setting of the alternatives below. • Ha: mƒm0 (m:ƒm0) • Ha: mm0) TI-83 Plus Inferential Statistics and Distributions 397 item 2) performs a hypothesis test for a single unknown population mean m when the population standard deviation s is unknown. It tests the null hypothesis H0: m=m0 against one -sample t test; If you set the...
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2.SampZTest 2.SampZTest (two-sample z test; 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 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.
2.SampZTest 2.SampZTest (two-sample z test; 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 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.
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item 4) tests the equality of the means of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) TI-83 Plus Inferential Statistics and Distributions 400 The null hypothesis H0: m1=m2 is tested against one of two populations (m1 and m2) based on independent samples when neither population standard deviation (s1 or s2) is known. Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test;
item 4) tests the equality of the means of the alternatives below. • Ha: m1ƒm2 (m1:ƒm2) • Ha: m1m2) TI-83 Plus Inferential Statistics and Distributions 400 The null hypothesis H0: m1=m2 is tested against one of two populations (m1 and m2) based on independent samples when neither population standard deviation (s1 or s2) is known. Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test;
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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. The computed confidence interval depends on the user-specified confidence level. ZInterval ZInterval (one-sample z confidence interval;
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. The computed confidence interval depends on the user-specified confidence level. ZInterval ZInterval (one-sample z confidence interval;
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The computed confidence interval depends on the user-specified confidence level. 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 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.
The computed confidence interval depends on the user-specified confidence level. 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 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.
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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. 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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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. 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;
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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).
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...inputs in this chapter. Summary statistics (mean that they appear in the same order that you are testing. The name of the population mean , standard deviation, and sample size) for these inputs in List. Input m0 s List Freq Calculate/Draw v, Sx, n s1 Description Hypothesized value of the... tests, Draw draws a graph of the results. Must be a real number > 0. All elements must be a real number > 0. The known population standard deviation from the first population for the data in the inferential stat editors. TI-83 Plus Inferential Statistics and Distributions 419
...inputs in this chapter. Summary statistics (mean that they appear in the same order that you are testing. The name of the population mean , standard deviation, and sample size) for these inputs in List. Input m0 s List Freq Calculate/Draw v, Sx, n s1 Description Hypothesized value of the... tests, Draw draws a graph of the results. Must be a real number > 0. All elements must be a real number > 0. The known population standard deviation from the first population for the data in the inferential stat editors. TI-83 Plus Inferential Statistics and Distributions 419
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...standard deviation, and n2 sample size) for the two-sample tests and intervals. Must be an integer , 0. Yes instructs the TI.83 to pool the variances. x1 The count of successes from the second population for the 1.PropZTest and 1.PropZInt. Must be a real number, such that 0 < p0 < 1. TI-83 Plus... Inferential Statistics and Distributions 420 Defaults=1. Must be integers | 0. All elements must be an integer > 0. No instructs the TI.83 not to pool the variances. List1, List2 The names of observations in ...
...standard deviation, and n2 sample size) for the two-sample tests and intervals. Must be an integer , 0. Yes instructs the TI.83 to pool the variances. x1 The count of successes from the second population for the 1.PropZTest and 1.PropZInt. Must be a real number, such that 0 < p0 < 1. TI-83 Plus... Inferential Statistics and Distributions 420 Defaults=1. Must be integers | 0. All elements must be an integer > 0. No instructs the TI.83 not to pool the variances. List1, List2 The names of observations in ...
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...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