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docker41 [41]
3 years ago
14

The graph shows the amount of rainfall in a town in July over a

Mathematics
1 answer:
Rus_ich [418]3 years ago
4 0

Answer:30%

Step-by-step explanation:

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Murrr4er [49]
Here is a picture of the answer:

6 0
3 years ago
Find the midpoint of NP⎯⎯⎯⎯⎯ given N(2a, 2b) and P(2a, 0).
geniusboy [140]

Answer:

(2a, b )

Step-by-step explanation:

Given the endpoints (x₁, y₁ ) and (x₂, y₂ ) then the midpoint is

[ \frac{1}{2}(x₁ + x₂ ), \frac{1}{2}(y₁ + y₂ ) ]

Here (x₁, y₁ ) = N(2a, 2b) and (x₂, y₂ ) = P(2a, 0), thus

midpoint = [ \frac{1}{2}(2a + 2a), \frac{1}{2}(2b + 0 ) ] = (2a, b )

4 0
3 years ago
A store had a number of chairs in stock at the beginning of the week. During the week, 66 chairs were sold, leaving the store wi
Ann [662]
They had 81 chairs at the beginning
6 0
3 years ago
Read 2 more answers
Dylan Rieder is a statistics student investigating whether athletes have better balance than non-athletes for a thesis project.
Kobotan [32]

Answer:

t=\frac{(3.7-4.1)-0}{\sqrt{\frac{1.1^2}{32}+\frac{1.3^2}{45}}}}=-1.457

p_v =P(t_{75}  

Comparing the p value with a significance level for example \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can't say that the population mean for the athletes is significantly lower than the population mean for non athletes.  

Step-by-step explanation:

Data given and notation

\bar X_{A}=3.7 represent the mean for athletes  

\bar X_{NA}=4.1 represent the mean for non athletes  

s_{A}=1.1 represent the sample standard deviation for athletes  

s_{NA}=1.3 represent the sample standard deviation for non athletes

n_{A}=32 sample size for the group 2  

n_{NA}=45 sample size for the group 2  

\alpha=0.01 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 population mean for athletes is lower than the population mean for non athletes, the system of  hypothesis would be:  

Null hypothesis:\mu_{A}-\mu_{NA}\geq 0  

Alternative hypothesis:\mu_{A} - \mu_{NA}< 0  

We don't have the population standard deviation's, we can apply a t test to compare means, and the statistic is given by:  

t=\frac{(\bar X_{A}-\bar X_{NA})-\Delta}{\sqrt{\frac{s^2_{A}}{n_{A}}+\frac{s^2_{NA}}{n_{NA}}}} (1)  

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:  

t=\frac{(3.7-4.1)-0}{\sqrt{\frac{1.1^2}{32}+\frac{1.3^2}{45}}}}=-1.457

P value  

We need to find first the degrees of freedom given by:

df=n_A +n_{NA}-2=32+45-2=75

Since is a one left tailed test the p value would be:  

p_v =P(t_{75}  

Comparing the p value with a significance level for example \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can't say that the population mean for the athletes is significantly lower than the population mean for non athletes.  

5 0
3 years ago
Create a square root with at least 3 transformations
Fittoniya [83]

Answer:

Step-by-step explanation:

Start with f(x) = √x.

1) Multiplying this by "c" will either stretch or shrink the graph:  stretch, if "c" is > 0; shrink, if 0 < c < 1.

2) Replacing 'x' with 'x - h' will translate the original graph h units to the right, if h is positive;

Replacing 'x' with 'x - h' will translate the original graph h units to the left, if h is negative.

3) Adding k to f(x) = √x will translate the graph upward by k units if k is positive and downward by k units if k is negative.

8 0
3 years ago
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