What we know:
Petrolyn motor oil is a combination of natural oil and synthetic oil. It contains 7 liters of natural oil for every 5 liters of synthetic oil.
What we need to find:
If 355 liters of synthetic oil are used, how many liters of petrolyn oil will be made?
Set up a proportion to find how much natural oil is used.
7L natural oil/5L synthetic oil = x/355 synthetic oil where x=natural oil
7/5=x/355
(5)(x)=(7)(355) cross multiplied
5x=2485 simplified
5/5x=2485/5 multiplicative inverse
x=497L
Now, add both synthetic oil and natural oil to find amount of petrolyn oil.
355 L synthetic oil + 497 L natural oil= 852 L of petrolyn oil
First, put the numbers in order
A. 1,2,3,4,5,7,8,8,9.....median (middle number) is 5..when there is an odd number of data values, there will only be one median.
B. 14,14,15,16,17,18,19,20....if there is an even number of data points, there will be 2 middle numbers. In that case, u add the 2 middle numbers and divide by 2 to find the median. (16 + 17) / 2 = 33/2 = 16.5 is ur median.
Answer:
a) The 99% confidence interval is from 14.8% to 23.2%.
b) The confidence interval tells us that the true proportion of mislabeled is within 14.8% and 23.2%, with a 99% confidence. In other words, if we take samples of the same size, 99% of the samples will have a proportion within 0.148 and 0.232.
c) The confidence interval calculation take into account the sample size, so the width (or precision) of the interval depends on the sample size.
The only criticism that could be analyzed is to see if the sample is representative of the population.
Step-by-step explanation:
a) We have to calculate a 99% confidence interval for the proportion.
The sample proportion is p=0.19.
The standard error of the proportion is:
The critical z-value for a 99% confidence interval is z=2.576.
The margin of error (MOE) can be calculated as:
Then, the lower and upper bounds of the confidence interval are:
The 99% confidence interval for the population proportion is (0.148, 0.232).
Answer:
False
Step-by-step explanation:
Correlation measures the strength of the relation between two variables.
Further, Correlation is said to be positive if increasing/decreasing the one variable, also increases/decreases the values of another variable.
Correlation is said to be negative if increasing/decreasing the one variable, also decreases/increases the values of another variable.
Since we don't know here exists a positive correlation or negative correlation.
So here are two possible conditions:
The person who has Gum disease also has heart disease.
And, the person has Gum disease can never have heart disease.
Thus, the given statement is false.
