<h3>The y intercept is
-1</h3>
We can say that the y intercept is at the location (0,-1)
This is where the graph crosses the vertical y axis. This is 1 unit below the origin.
This is assuming each tickmark on the grid represents 1 unit.
<u>Given: </u>
- Breadth of canvas is 22 inches.
- Length of canvas is 38 inches.
<u>To Find:</u>
- If kendra covered 30% of the canvas by painting red rose, what will be the area of canvas covered by red rose?
<u>Solution: </u>
To find the area of red rose, first we have to find the area of canvas.
★ Area of Rectangle = Length × Breadth
➝ 22 × 38
➝ 836 in²
So, Area of canvas is 836 inches².
★ Area of red rose:-
➝ 30% of 836 in²
➝ 0.30 of 836
➝ 250.8
Hence, Area covered by the red rose is <u>2</u><u>5</u><u>0</u><u>.</u><u>8</u>
<h2> ____________________</h2><h3><u>Additional</u><u> </u><u>Information:</u><u> </u></h3>
★ Triangle => ½bh
★ Rectangle => Length × Breadth
★ Circle => πr²
★ Square => Side × Side
★ Parallelogram => Base × Height
★ Sphere => 4πr²
Answer:
<h3>In an independent groups experiment, if we must estimate the population standard deviation to determine the significance of the sample results, the appropriate inference test is the<u> t test</u></h3>
Step-by-step explanation:
In an independent groups experiment, if we must estimate the population standard deviation to determine the significance of the sample results, the appropriate inference test is the<u> </u><u>t test</u>
<h3>For :</h3>
- A t-test is one of the methods of a statistic and is used to determine if there is a significant difference between the two groups of their means based on a sample in data.
- The statistical significance is determined by the difference between the averages of group size , the sample size, and standard deviations of the groups.
<h3>Therefore option c) t test is correct</h3>
Answer:
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Step-by-step explanation:
I am mad don't know
It's correlation. A causal relationship between two events exist if the occurrence of the first causes the other. The first event is called the cause and the second event is called the effect. A correlation between two variables does not imply causation. It may sound complicated but think of it like this. They are co related but they don't really effect one another, they just happen to occur at the same time. I really hope this helps. Let me know if I got anything wrong ok!
