Answer:
interest: 1,800
total: 13,800
Step-by-step explanation:
Number 16 is D & 15 is D because in number 16 8y can’t equal X but 8 can be in the X&Y’s place. As for number 15 the correct equation is 2y=0-4. Add to 2y and the equation is left with 2y=-4 divide that and you get a positive 2. Pls make my answer the Brainliest, I would rlly appreciate it...Please and Thank You!
The true statement about the residual plot is (a) The regression line is a good model because there is no pattern in the residuals.
<h3>How to interpret the residual plot?</h3>
For a residual plot to be considered a good model, the points on the plot must be at random and they must not follow a specific pattern
From the graph, we can see that the points are scattered
Hence, the true statement about the residual plot is (a)
Read more about residual plots at:
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Answer:
y = 2x + 1
Step-by-step explanation:
You can see a pattern in the group of x's that the numbers go up by 1 Also in the y-set that the numbers go up by 2. So this pattern is linear, that means the "rule" you are looking for does not have exponents or square roots or any very complicated stuff. You can use a guess and check method. Say to yourself how can I get a 7 out, when I put a 3 in? "times by2 and plus 1" works.
3 times 2, and plus1
gives you 7.
Test it on the other numbers.
-1 times2, and plus1
2(-1)+1 = -1
2(0)+1 = 1
2(1)+1 = 3
2(2)+1 = 5
It works for all the numbers.
You can calculate it also, using any two pairs of (x,y) from the data set. Put y-y on top of a fraction and x-x on the bottom. You will get the slope and that is the 2 in the "rule"
(3,7) and (2,5) for example. 7-5 so put 2 on top and 3-2 so put 1 on the bottom. 2/1 is just 2. From the point (0,1) we know the y-intercept is 1. This also gives the equation y=2x+1.
If you are just starting to learn this, probably just guess and check a rule. The rule has to work for all the points.
Answer:
A statistic is said to be unbiased if the mean of its sampling distribution is equal to the true value of the parameter being estimated.
Step-by-step explanation:
A parameter is a number that describes the population.
A statistic is a number that describes a sample.
A statistic used to estimate a parameter is unbiased if the mean of its sampling distribution is exactly equal to the true value of the parameter being estimated. For example, the mean of a sample is an unbiased estimate of the mean of the population from which the sample was drawn.
A statistic is biased if its expected value is not equal to the parameter.
