The color that has the greatest difference between the theoretical and experimental probability is yellow.
<h3>Which color has the greatest difference?
</h3>
Theoretical probability of each color = number of color in each section / total number of sections
1/5 = 0.2
Experimental probability is based on the result of an experiment that has been carried out multiples times
Experimental probability
Experimental probability of choosing orange = 118 / 625 = 0.19
Difference = 0.2 - 0.19 = 0.01
Experimental probability of choosing purple = 137 / 625 = 0.22
Difference 0.22 - 0.2 = 0.02
Experimental probability of choosing brown = 122 / 625 = 0.20
0.2 - 0.2 = 0
Experimental probability of choosing yellow = 106 / 625 = 0.17
0.20 - 0.1696 = 0.0304
Experimental probability of choosing green = 142 / 625 = 0.23
0.2272 - 0.20 = 0.0272
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180-2(55)-x=0
180-110-x=0
70-x=0
-x=-70
x=70°
Fractions. Is your answers
Using the normal distribution, it is found that there is a 0.0005 = 0.05% probability of getting more than 66 heads.
<h3>Normal Probability Distribution</h3>
The z-score of a measure X of a normally distributed variable with mean 
and standard deviation 
is given by:
- The z-score measures how many standard deviations the measure is above or below the mean.
- Looking at the z-score table, the p-value associated with this z-score is found, which is the percentile of X.
- The binomial distribution is the probability of x successes on n trials, with p probability of a success on each trial. It can be approximated to the normal distribution with
.
For the binomial distribution, the parameters are given as follows:
n = 100, p = 0.5.
Hence the mean and the standard deviation of the approximation are given as follows:
.
Using continuity correction, the probability of getting more than 66 heads is P(X > 66 + 0.5) = P(X > 66.5), which is <u>one subtracted by the p-value of Z when X = 66.5</u>.
Z = 3.3
Z = 3.3 has a p-value of 0.9995.
1 - 0.9995 = 0.0005.
0.0005 = 0.05%
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