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Returns median of a list. Returns standard deviation of a list. LIST MATH Menu LIST MATH Menu To display the LIST MATH menu, press y 9 |. Returns mean ( 4:median( 5:sum( 6:prod( 7:stdDev( 8:variance( Returns minimum element ... or larger of each pair of a list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns the variance of listA. TI-83 Plus Lists 311 min(, max( min( (minimum) and max( (maximum) return the smallest or largest element of a list. Returns maximum element of elements in a list. NAMES...
Returns median of a list. Returns standard deviation of a list. LIST MATH Menu LIST MATH Menu To display the LIST MATH menu, press y 9 |. Returns mean ( 4:median( 5:sum( 6:prod( 7:stdDev( 8:variance( Returns minimum element ... or larger of each pair of a list. For a complex list, the element with smallest or largest magnitude (modulus) is returned. Returns the variance of listA. TI-83 Plus Lists 311 min(, max( min( (minimum) and max( (maximum) return the smallest or largest element of a list. Returns maximum element of elements in a list. NAMES...
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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. Each freqlist element counts the number of consecutive occurrences of the elements in ... are not valid. 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 Complex lists are not valid.
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. Each freqlist element counts the number of consecutive occurrences of the elements in ... are not valid. 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 Complex lists are not valid.
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...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 y minimum of x ...... Statistical Variables The statistical variables are cleared. To access these variables for use in the column below . If you edit a list or change the type of analysis, all statistical variables are calculated and...
...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 y minimum of x ...... Statistical Variables The statistical variables are cleared. To access these variables for use in the column below . If you edit a list or change the type of analysis, all statistical variables are calculated and...
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... generated from a normally distributed 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
... generated from a normally distributed 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
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The actual mean þ of 163.8 and sample standard deviation Sx of the intervals calculated to compute this interval. Use a sample mean of the population sampled is 165.1 centimeters, which is in a very large number ... sample þ used to contain the population mean. The .99 confidence level indicates that in the calculated interval. The third line gives the sample standard deviation Sx. TI-83 Plus Inferential Statistics and Distributions 384 The second line gives the mean height of women's heights, increase the sample size to 90. The bottom line gives...
The actual mean þ of 163.8 and sample standard deviation Sx of the intervals calculated to compute this interval. Use a sample mean of the population sampled is 165.1 centimeters, which is in a very large number ... sample þ used to contain the population mean. The .99 confidence level indicates that in the calculated interval. The third line gives the sample standard deviation Sx. TI-83 Plus Inferential Statistics and Distributions 384 The second line gives the mean height of women's heights, increase the sample size to 90. The bottom line gives...
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TI-83 Plus Inferential Statistics and Distributions 385 Press 90 Í to store 90 to clear the home screen. Press ' to n. 9. Press y = to ü. 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...
TI-83 Plus Inferential Statistics and Distributions 385 Press 90 Í to store 90 to clear the home screen. Press ' to n. 9. Press y = to ü. 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...
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Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. Ans (175.5448205 from step 11) is the lower bound. 1å99 is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. The normal curve is the upper bound. 14. Press Í to the home screen. up is the lower bound. TI-83 Plus Inferential Statistics and Distributions 387 low is the upper bound. Area is the area above the 95th percentile. Press Í to paste ShadeNorm( to plot and shade the normal curve.
Press y Z ¢ 1 y D 99 ¢ 165 Ë 1 ¢ 6 Ë 35 ¤. Ans (175.5448205 from step 11) is the lower bound. 1å99 is defined by a mean µ of 165.1 and a standard deviation σ of 6.35. 15. The normal curve is the upper bound. 14. Press Í to the home screen. up is the lower bound. TI-83 Plus Inferential Statistics and Distributions 387 low is the upper bound. Area is the area above the 95th percentile. Press Í to paste ShadeNorm( to plot and shade the normal curve.
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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 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;
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...: 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 T.Test T.Test (one of 4 (Chapter 1). If you set the decimal mode to Float or a different fixed-decimal setting, your output... the examples. 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.
...: 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 T.Test T.Test (one of 4 (Chapter 1). If you set the decimal mode to Float or a different fixed-decimal setting, your output... the examples. 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.
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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; 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
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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 Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test; 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.
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 Calculated results: , , Drawn results: 2.SampTTest 2.SampTTest (two-sample t test; 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.
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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. 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 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. 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 ZInterval ZInterval (one-sample z confidence interval;
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The computed confidence interval depends on the user-specified confidence level. 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 TInterval TInterval (one-sample t confidence interval;
The computed confidence interval depends on the user-specified confidence level. 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 TInterval TInterval (one-sample t confidence interval;
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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. 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;
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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 The computed confidence interval depends on the userspecified confidence level. Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval;
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 The computed confidence interval depends on the userspecified confidence level. Calculated results: 2.SampTInt 2.SampTInt (two-sample t confidence interval;
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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). 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;
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... output to generate for the two-sample tests and intervals. All elements must be integers | 0. Determines the type of the population mean , standard deviation, and sample size) for the data in List. In tests, Draw draws a graph of the list containing the data you are testing.... Statistics Input Descriptions The tables in this section describe the inferential statistics inputs discussed in the inferential stat editors. The known population standard deviation; TI-83 Plus Inferential Statistics and Distributions 419 You enter values for these inputs in this chapter.
... output to generate for the two-sample tests and intervals. All elements must be integers | 0. Determines the type of the population mean , standard deviation, and sample size) for the data in List. In tests, Draw draws a graph of the list containing the data you are testing.... Statistics Input Descriptions The tables in this section describe the inferential statistics inputs discussed in the inferential stat editors. The known population standard deviation; TI-83 Plus Inferential Statistics and Distributions 419 You enter values for these inputs in this chapter.
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...integers | 0. Yes instructs the TI.83 to pool the variances. TI-83 Plus Inferential Statistics and Distributions 420 n The count of observations in the two- All elements must be a real number > 0. Defaults=1. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for...Freq1, Freq2 The names of the lists containing the data you are L1 and L2, respectively. Input Description s2 The known population standard deviation from sample one and sample two in the sample for the 1.PropZTest and 1.PropZInt. Must be a real number, such that ...
...integers | 0. Yes instructs the TI.83 to pool the variances. TI-83 Plus Inferential Statistics and Distributions 420 n The count of observations in the two- All elements must be a real number > 0. Defaults=1. v1, Sx1, n1, v2, Sx2, Summary statistics (mean, standard deviation, and n2 sample size) for...Freq1, Freq2 The names of the lists containing the data you are L1 and L2, respectively. Input Description s2 The known population standard deviation from sample one and sample two in the sample for the 1.PropZTest and 1.PropZInt. Must be a real number, such that ...
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... 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 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 .
... 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 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 .
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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