A money box contains only 10-cent
1 answer:
Answer:
Number of 10 cents = 18
Number of 20 cents = 10
Step-by-step explanation:
Let number of 10 cents be = x
Let number 20 cents be = y
Total number of coins = x + y = 28 -------- ( 1 )
Total amount in the box = 0.10 x + 0.20y = 3.80 ---------- ( 2 )
<em><u>Solve the equations to find x and y</u></em>
( 1 ) => x + y = 28
x = 28 - y
Substitute x in ( 2 )
( 2 ) => 0.10(28 - y) + 0.20y = 3.80
2.80 - 0.10y + 0.20y = 3.80
0.10 y = 3.80 - 2.80
0.10 y = 1.00
y = 10
Substitute y in ( 1 ) => x + y = 28
x + 10 = 28
x = 28 - 10
x = 18
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In statistics, the standard deviation deviation may be a measure of the quantity of variation or dispersion of a group of values. The margin of error may be a statistic expressing the number of sampling error within the results of a survey. The correlation could be a statistical measure of the strength of the connection between the relative movements of two variables.
Given nothing and that we need to explain standard deviation. margin of error, correlation coefficient .
Standard deviation
In statistics, the standard deviation may be a measure of the number of variation or dispersion of a group of values. an occasional variance indicates that the values tend to be near the mean of the set, while a high variance indicates that the values are detached over a wider range.
Formula:
where x bar is mean and N is size of population.
Margin of error
The margin of error may be a statistic expressing the quantity of sampling error within the results of a survey. The larger the margin of error, the less confidence one should have that a poll result would reflect the results of a survey of the complete population.
Formula for M=z*s/
here z is z value of Z score , s is variance , n is that the sample size.
Correlation coefficient
In statistics, the Pearson parametric statistic ― also called Pearson's r, the Pearson product-moment parametric statistic, the bivariate correlation, or colloquially simply because the coefficient of correlation ― could be a measure of linear correlation between two sets of information.
Formula=∑∑
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Learn more about correlation coefficient at brainly.com/question/4219149
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