6.2 ÷ 3.1 is equivalent to 62 ÷ 31 The dividend and divisor were both multiplied by
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Answer:
a) The 95% confidence interval would be given (0.0702;0.1098).
We can conclude that the true population proportion at 95% of confidence is between (0.0702;0.1098)
b) Since the confidence interval NOT contains the value 0.06 we have anough evidence to reject the claim at 5% of significance.
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
represent the real population proportion of interest
represent the estimated proportion for the sample
n=800 is the sample size required
represent the critical value for the margin of error
Confidence =0.95 or 95%
Part a
The population proportion have the following distribution
The confidence interval would be given by this formula
For the 95% confidence interval the value of and
, with that value we can find the quantile required for the interval in the normal standard distribution.
The margin of error is given by :
And replacing into the confidence interval formula we got:
And the 95% confidence interval would be given (0.0702;0.1098).
We can conclude that the true population proportion at 95% of confidence is between (0.0702;0.1098)
Part b
Since the confidence interval NOT contains the value 0.06 we have anough evidence to reject the claim at 5% of significance.
Answer:
Correct statement: (a) and (b).
Step-by-step explanation:
R-squared is a statistical quantity that measures, just how near the values are to the fitted regression line. It is also known as the coefficient of determination.
The coefficient of determination is the squared value of the correlation coefficient.
That is,
The correlation coefficient between two variables is the measure of the strength and direction of the relationship between two variables.
Its values ranges from -1.00 to +1.00.
Although <em>r</em> can be negative but R² is always positive, since square of a negative number is also positive.
So the correct statements are:
a. cannot be negative
b. is the square root of the coefficient of correlation