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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Answer:
Yes
Step-by-step explanation:
Graph this function on your calculator and you will see an upwards graph, if the range (y), -1 can be mapped on the graph, it is within the range.
Asked and answered elsewhere.
brainly.com/question/1410592_____
Google doesn't recognize the terms "defects method" except in association with various postings of this same problem.
Answer:
225 frogs
Step-by-step explanation:
Total population of frogs = 300 frogs.
Observed population of frogs = 24
6 of the 24 observed frogs had spots
Which means , the number of frogs that did not have spots = 24 - 6 = 18 frogs.
We were told to find how many of the total population can be predicted to NOT have spots. We would form a proportion.
If 24 frogs = 18 frogs with no spots
300 frogs = Y
Cross multiply
24Y = 300 × 18
Y = (300 × 18) ÷ 24
Y = 5400 ÷ 24
Y = 225 frogs.
This means out of 300 frogs, 225 frogs do not have spots.
Therefore, the total population that can be predicted to NOT have spots is 225 frogs.
the total population can be predicted to NOT have spots
Ok first we have to find out whats 2p+p=20 combine like terms to get 3p=20 the divide 3 on each side to get p=6 2/3 then we plug in 6 2/3 to 2p-5 so 2(6 2/3) -5 so its 12.666-5 to get 7.666 so that's the answer.