What does the term epicenter refer to?

One factor of 7x2 + 33x – 10 is

stiv31 [10]

$7x^{2} +33x-10=0$

$\implies 7x^{2} +35x-2x-10=0\\\implies7x(x+5)-2(x+5)=0\\\implies (7x-2)(x+5)=0$

$7x - 2 = 0\\\implies \boxed{\bold{x = \frac{2}{7} }}$

$x+5=0\\\implies \boxed{\bold{x=-5}}$

6 0

3 years ago

The number of events is 29, the number of trials is 298, the claimed population proportion is 0.10, and the significance leve

Nina [5.8K]

Answer:

$z=\frac{0.0973 -0.1}{\sqrt{\frac{0.1(1-0.1)}{298}}}=-0.155$

$p_v =2*P(Z$

And we can use excel to find the p value like this: "=2*NORM.DIST(-0.155;0;1;TRUE)"

So the p value obtained was a very high value and using the significance level given $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of interest is not significantly different from 0.1 .

Step-by-step explanation:

1) Data given and notation

n=298 represent the random sample taken

X=29 represent the events claimed

$\hat p=\frac{29}{298}=0.0973$ estimated proportion

$p_o=0.1$ is the value that we want to test

$\alpha=0.05$ represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

2) Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the proportion is 0.1 or no.:

Null hypothesis: $p=0.1$

Alternative hypothesis: $p \neq 0.1$

When we conduct a proportion test we need to use the z statistic, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

3) Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.0973 -0.1}{\sqrt{\frac{0.1(1-0.1)}{298}}}=-0.155$

4) Statistical decision

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(Z$

And we can use excel to find the p value like this: "=2*NORM.DIST(-0.155;0;1;TRUE)"

So the p value obtained was a very high value and using the significance level given $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of interest is not significantly different from 0.1 .

We can do the test also in R with the following code:

> prop.test(29,298,p=0.1,alternative = c("two.sided"),conf.level = 1-0.05,correct = FALSE)

7 0

3 years ago

What is the measure of

Aneli [31]

Not sure what the measure of ____ is, can you specify?

8 0

3 years ago

Please help with this look below! : )

kykrilka [37]

Answer:

$0.40

Step-by-step explanation:

5.60/14 = .40

5 0

3 years ago

The distribution of the test statistic for analysis of variance is the F-distribution. true or false

lubasha [3.4K]

Answer:

True. See explanation below

Step-by-step explanation:

Previous concepts

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"

If we assume that we have $k$ groups and on each group from $j=1,\dots,k$ we have $k$ individuals on each group we can define the following formulas of variation: