Calculate each value for ⊙P. Use 3.14 for π and round to the nearest tenth.
1 answer:
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Answer:
Step-by-step explanation:
We will let the x coordinates be the temp and the y coordinates by the number of chirps. Our coordinates then will look like this:
(60, 84) and (85, 184). If this is linear, then first we will find the slope of the line which will tell us, in the context of this problem, how many chirps a cricket gives per 1 degree of temp increase.
The slope formula is:
and filling in our numbers:
This means that for every 1 degree temp increase, a cricket will give 4 chirps. That's the m value in y = mx + b. Now we will pick one of the coordinates, doesn't matter which one, and use those x and y values in the point-slope form of a line to get the equation. I will choose (60, 85), just because. Using the other point will give you the exact same line equation, I PROMISE!
Using 85 as y1 and 60 as x1 in
y - y1 = m(x - x1) gives us
y - 85 = 4(x - 60) and
y - 85 = 4x - 240 and
y = 4x - 240 + 85 and
y = 4x - 155
Answer:
Comparing the p value with a significance level for example we see that
so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.
Step-by-step explanation:
Data given and notation
represent the mean for A
represent the mean for B
represent the sample standard deviation for A
represent the sample standard deviation for B
sample size for the group A
sample size for the group B
Significance level provided
t would represent the statistic (variable of interest)
Concepts and formulas to use
We need to conduct a hypothesis in order to check if the means are equal or not, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
We don't have the population standard deviation's but we assume that the population deviation is equal for both populations, so we can apply a t test to compare means, and the statistic is given by:
(1)
Where represent the standard deviation pooled given by:
t-test: Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other.
With the info given we can replace in formula (1) like this:
P value
We need to find first the degrees of freedom given by:
Since is a two tailed test the p value would be:
Comparing the p value with a significance level for example we see that
so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.