The population correlation coefficient is significant if the correlation is closer to 1, less significant is closer to zero, and not significant at all if the correlation coefficient is zero.
- Correlation coefficients are used in determining the significance of a population and the strength of the relationship <u>between two variables. </u>
- This relationship can either be strong, weak, or not exist.
- The correlation coefficient can have values between 0 and 1 inclusive. The population correlation coefficient is significant if the correlation is closer to 1, less significant is closer to zero, and not significant at all if the correlation coefficient is zero.
Learn more on correlation here: brainly.com/question/13879362
It is linear through a:
Table: the y values have a constant rate of change. For example the y values would be 7, 14, 21, 28 going up by 7 each time. This would not be an example: 6, 12, 17, 18.
Graph: The line of the graph is straight!
Equation: It is in y=mx+b or slope intercept form. Hope this helps!
Fist lets find the % of people using boats
100%- (36+53+2)= 9%
then find the number of people of 9%
200= 100%
B=9%
100B=200x9
B= 18
Answer:
It's the bottom one
Step-by-step explanation:
I got it wrong on the IXL, but the explanation says so. If someone can help me, please do because I have no idea how to do these
Answer: About 0.8034 of the items will be classified as good.
Step-by-step explanation:
Let's first understand that because 13% of the items are defective, that means 87% of the items are not defective. And because the inspector incorrectly classifies the items 9% of the time, it's important to understand that that means both the defective and the not defective items may be incorrectly classified. In order to figure out what proportion will be classified as 'good,' let's set up a tree diagram:
--0.13--defective
|__0.09__ classified as 'good'
|__0.91__ classified as 'defective'
--0.87--not defective
|__0.09__ classified as 'defective'
|__0.91__classified as 'good'
This chart essentially reiterates the information in the prompt, showing that 9% of each type of item will be incorrectly classified. Now we need to find the proportion of items that will be classified as 'good.' To do this, we must multiply the proportion of items classified as 'good' by the proportion of items that are either defective or not defective for both types, like this:
(0.13 * 0.09) + (0.87 * 0.91)
this expression in words means: "13% of the items will be classified as good 9% of the time, and the other 87% of the items will be classified as good 91% of the time"
When we multiply and add these numbers together, we get 0.8034, but you should round to 2 or 3 decimal places like the prompt instructs. Hope this helped! :)
