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Solution - Cumulative probability in the standard normal distribution

Cumulative probability 74.555%
74.555%

Step-by-step explanation

1. Find the cumulative probability of the z-scores values up to 0.382

Use the positive z-table to find the value corresponding to 0.382. This value is the cumulative probability of the area to the left of 0.382.

Z0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
0.00.50.503990.507980.511970.515950.519940.523920.52790.531880.53586
0.10.539830.54380.547760.551720.555670.559620.563560.567490.571420.57535
0.20.579260.583170.587060.590950.594830.598710.602570.606420.610260.61409
0.30.617910.621720.625520.62930.633070.636830.640580.644310.648030.65173
0.40.655420.65910.662760.66640.670030.673640.677240.680820.684390.68793
0.50.691460.694970.698470.701940.70540.708840.712260.715660.719040.7224
0.60.725750.729070.732370.735650.738910.742150.745370.748570.751750.7549
0.70.758040.761150.764240.76730.770350.773370.776370.779350.78230.78524
0.80.788140.791030.793890.796730.799550.802340.805110.807850.810570.81327
0.90.815940.818590.821210.823810.826390.828940.831470.833980.836460.83891
1.00.841340.843750.846140.848490.850830.853140.855430.857690.859930.86214
1.10.864330.86650.868640.870760.872860.874930.876980.8790.8810.88298
1.20.884930.886860.888770.890650.892510.894350.896170.897960.899730.90147
1.30.90320.90490.906580.908240.909880.911490.913080.914660.916210.91774
1.40.919240.920730.92220.923640.925070.926470.927850.929220.930560.93189
1.50.933190.934480.935740.936990.938220.939430.940620.941790.942950.94408
1.60.94520.94630.947380.948450.94950.950530.951540.952540.953520.95449
1.70.955430.956370.957280.958180.959070.959940.96080.961640.962460.96327
1.80.964070.964850.965620.966380.967120.967840.968560.969260.969950.97062
1.90.971280.971930.972570.97320.973810.974410.9750.975580.976150.9767
2.00.977250.977780.978310.978820.979320.979820.98030.980770.981240.98169
2.10.982140.982570.9830.983410.983820.984220.984610.9850.985370.98574
2.20.98610.986450.986790.987130.987450.987780.988090.98840.98870.98899
2.30.989280.989560.989830.99010.990360.990610.990860.991110.991340.99158
2.40.99180.992020.992240.992450.992660.992860.993050.993240.993430.99361
2.50.993790.993960.994130.99430.994460.994610.994770.994920.995060.9952
2.60.995340.995470.99560.995730.995850.995980.996090.996210.996320.99643
2.70.996530.996640.996740.996830.996930.997020.997110.99720.997280.99736
2.80.997440.997520.99760.997670.997740.997810.997880.997950.998010.99807
2.90.998130.998190.998250.998310.998360.998410.998460.998510.998560.99861
3.00.998650.998690.998740.998780.998820.998860.998890.998930.998960.999
3.10.999030.999060.99910.999130.999160.999180.999210.999240.999260.99929
3.20.999310.999340.999360.999380.99940.999420.999440.999460.999480.9995
3.30.999520.999530.999550.999570.999580.99960.999610.999620.999640.99965
3.40.999660.999680.999690.99970.999710.999720.999730.999740.999750.99976
3.50.999770.999780.999780.999790.99980.999810.999810.999820.999830.99983
3.60.999840.999850.999850.999860.999860.999870.999870.999880.999880.99989
3.70.999890.99990.99990.99990.999910.999910.999920.999920.999920.99992
3.80.999930.999930.999930.999940.999940.999940.999940.999950.999950.99995
3.90.999950.999950.999960.999960.999960.999960.999960.999960.999970.99997

A z-score of 0.382 corresponds to an area of 0.64803
p(z<0.382)=0.64803
The cumulative probability that z<0.382 is 64.803%

2. Find the cumulative probability of the z-scores values greater than 0.382

To find the cumulative probability of the values greater than 0.382, we need to subtract the cumulative probability of the values less than 0.382 from the total probability under the curve, which is equal to 1:

10.64803=0.35197
p(0.268>z>0.382)=0.35197
The cumulative probability of z>0.382 is 35.197%

3. Find the cumulative probability of the z-scores values up to 0.268

Use the negative z-table to find the value corresponding to -0.268. This value is the cumulative probability of the area to the left of -0.268.

Z0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09
-3.90.000050.000050.000040.000040.000040.000040.000040.000040.000030.00003
-3.80.000070.000070.000070.000060.000060.000060.000060.000050.000050.00005
-3.70.000110.00010.00010.00010.000090.000090.000080.000080.000080.00008
-3.60.000160.000150.000150.000140.000140.000130.000130.000120.000120.00011
-3.50.000230.000220.000220.000210.00020.000190.000190.000180.000170.00017
-3.40.000340.000320.000310.00030.000290.000280.000270.000260.000250.00024
-3.30.000480.000470.000450.000430.000420.00040.000390.000380.000360.00035
-3.20.000690.000660.000640.000620.00060.000580.000560.000540.000520.0005
-3.10.000970.000940.00090.000870.000840.000820.000790.000760.000740.00071
-3.00.001350.001310.001260.001220.001180.001140.001110.001070.001040.001
-2.90.001870.001810.001750.001690.001640.001590.001540.001490.001440.00139
-2.80.002560.002480.00240.002330.002260.002190.002120.002050.001990.00193
-2.70.003470.003360.003260.003170.003070.002980.002890.00280.002720.00264
-2.60.004660.004530.00440.004270.004150.004020.003910.003790.003680.00357
-2.50.006210.006040.005870.00570.005540.005390.005230.005080.004940.0048
-2.40.00820.007980.007760.007550.007340.007140.006950.006760.006570.00639
-2.30.010720.010440.010170.00990.009640.009390.009140.008890.008660.00842
-2.20.01390.013550.013210.012870.012550.012220.011910.01160.01130.01101
-2.10.017860.017430.0170.016590.016180.015780.015390.0150.014630.01426
-2.00.022750.022220.021690.021180.020680.020180.01970.019230.018760.01831
-1.90.028720.028070.027430.02680.026190.025590.0250.024420.023850.0233
-1.80.035930.035150.034380.033620.032880.032160.031440.030740.030050.02938
-1.70.044570.043630.042720.041820.040930.040060.03920.038360.037540.03673
-1.60.05480.05370.052620.051550.05050.049470.048460.047460.046480.04551
-1.50.066810.065520.064260.063010.061780.060570.059380.058210.057050.05592
-1.40.080760.079270.07780.076360.074930.073530.072150.070780.069440.06811
-1.30.09680.09510.093420.091760.090120.088510.086920.085340.083790.08226
-1.20.115070.113140.111230.109350.107490.105650.103830.102040.100270.09853
-1.10.135670.13350.131360.129240.127140.125070.123020.1210.1190.11702
-1.00.158660.156250.153860.151510.149170.146860.144570.142310.140070.13786
-0.90.184060.181410.178790.176190.173610.171060.168530.166020.163540.16109
-0.80.211860.208970.206110.203270.200450.197660.194890.192150.189430.18673
-0.70.241960.238850.235760.23270.229650.226630.223630.220650.21770.21476
-0.60.274250.270930.267630.264350.261090.257850.254630.251430.248250.2451
-0.50.308540.305030.301530.298060.29460.291160.287740.284340.280960.2776
-0.40.344580.34090.337240.33360.329970.326360.322760.319180.315610.31207
-0.30.382090.378280.374480.37070.366930.363170.359420.355690.351970.34827
-0.20.420740.416830.412940.409050.405170.401290.397430.393580.389740.38591
-0.10.460170.45620.452240.448280.444330.440380.436440.432510.428580.42465
0.00.50.496010.492020.488030.484050.480060.476080.47210.468120.46414

A z-score of 0.268 corresponds to an area of 0.39358
p(z<0.268)=0.39358
The cumulative probability that z<0.268 is 39.358%

4. Calculate the cumulative probability of the values greater than 0.382 and less than -0.268

Add the cumulative probability of the area to the right of the higher z-score (everything to the right of 0.382) to the cumulative probability of the area to the left of the lower z-score (everything to the left of -0.268):

0.35197+0.39358=0.74555
p(-0.268>z>0.382)=0.74555
The cumulative probability that -0.268>z>0.382 is 74.555%

Why learn this

The normal distribution is important because we see it often in nature. Suppose we gather many unrelated measures, like human heights, blood pressure readings, or IQ scores. They will follow the normal distribution.

We see many normally distributed variables in psychology. For example, reading ability, introversion or job satisfaction. In investing, the normal distribution shows asset class returns. Although these distributions are only roughly normal, they are pretty close, and we can treat them as normal.

The normal distribution is easy to work with. Many statistical tests rely on it. Moreover, these tests work well even when the distribution is only approximately normal. For example, if a set's mean and standard deviation are known, and the set follows the normal distribution, we can easily convert between percentiles and raw scores.

Any normal distribution can be standardized to a standard normal distribution. That way, we can compare two or more separate data sets. Using standard normal distribution, we can estimate probabilities of events involving normal distribution. This way, we can estimate how tall a person is likely to grow, for instance.