how to find the correlation on a ti-84?
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['To view the Correlation Coefficient, turn on "DiaGnosticOn" [2nd] "Catalog" (above the \'0\'). Scroll to DiaGnosticOn. [Enter] [Enter] again. ... ', 'Now you will be able to see the \'r\' and \'r^2\' values. Note: Go to [STAT] "CALC" "8:" [ENTER] to view. Prev: TI-84: Least Squares Regression Line (LSRL)']
245669
['Estimating the standard deviation, σ, of the sample data.', 'Multiplying that number by three.', 'Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL.']
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['Press 2ND and then VARS to display the DISTR menu. Select 3 and press ENTER to bring up the invNorm wizard screen.', 'Enter the desired percentile as a decimal next to the word area. ... ', 'Press Enter again, and the TI-84 Plus will calculate the z-score associated with the chosen percentile.']
110405
TI-84 models find square roots using a second function key. The square root function key is located above the x-squared (x2) key. To access the square root function, press the second function key (2nd) in the upper left corner of the key pad. Then press the x2 key and input the value to be evaluated.
1195589
In fact, the only difference is that the TI-84 has a mini-USB port while the TI-83 does not. Both calculators use the same type of central processing unit (CPU) (Zilog Z80), and the displays are the same (96 x 64 pixels). ... Both calculators have an I/O port but the TI-84 Plus also includes a mini-USB port.
18854
S(errors) = (SQRT(1 minus R-squared)) x STDEV. So, if you know the standard deviation of Y, and you know the correlation between Y and X, you can figure out what the standard deviation of the errors would be be if you regressed Y on X.
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['Find the mean of the data set.', 'Find the distance from each data point to the mean, and square the result.', 'Find the sum of those values.', 'Divide the sum by the number of data points.', 'Take the square root of that answer.']
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['Find the mean of all the x-values.', 'Find the standard deviation of all the x-values (call it sx) and the standard deviation of all the y-values (call it sy). ... ', 'For each of the n pairs (x, y) in the data set, take.', 'Add up the n results from Step 3.', 'Divide the sum by sx ∗ sy.']
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mx and my are the means of x and y variables. the p-value (significance level) of the correlation can be determined : by using the correlation coefficient table for the degrees of freedom : df=n−2. or by calculating the t value : t=r√1−r2√n−2.
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Newer TI 84's: Press STAT, choose CALC and press ENTER. You will see a display like the following. Make sure L1 is next to List: and L2 is next to FreqList:, then highlight Calculate and press Enter. The mean is next to , the sample standard deviation is next to Sx, and the population standard deviation is next to sx.
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=CORREL(A2:A11,B2:B11) A correlation coefficient of 0.998829 means there's a strong positive correlation between the two sets. As the 'X Variables' increase, the 'Y Variables' increases also.
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['Calculate the mean.', 'Calculate the standard deviation using the formula: s= √ ((∑ X(squared)/N)–X-bar)', 'Calculate the standard error of the mean using the formula: s/√ N-1.', 'Determine the value of T from the t-table.']
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Just use abs(x - y) . This'll return the net difference between the two as a positive value, regardless of which value is larger. Please share simpler or more pythonic approaches, if you have one.
1016340
['A = (sector angle / 360 ) * (pi *r2)', 'A = (sector angle / (2*pi)) * (pi * r2)', 'A = (fraction of the circle) * (pi * r2)']
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Find the product of the z-scores by multiplying each of the pairs of z-scores (zxzy). Then sum the products (S zxzy). Finally, divide the sum of the products by the number of scores (n) to find the correlation coefficient, r. Recall that z scores have a mean of zero.
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Divide the sum by sx ∗ sy. Divide the result by n – 1, where n is the number of (x, y) pairs. (It's the same as multiplying by 1 over n – 1.) This gives you the correlation, r.
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['Compute alpha (α): α = 1 - (confidence level / 100)', 'Find the critical probability (p*): p* = 1 - α/2.', 'To express the critical value as a z-score, find the z-score having a cumulative probability equal to the critical probability (p*).', 'To express the critical value as a t statistic, follow these steps.']