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3 years ago

Is this correct? H^3•h^4•k=h^12•k

Mathematics

2 answers:

andriy [413]3 years ago

7 0

No it is incorrect try rearranging things

jenyasd209 [6]3 years ago

5 0

Answer:

Step-by-step explanation:

We can use the rule [ x^y * x^z = x^y+z ]

h^3 * h^4

h^3+4

h^7

Best of Luck!

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I don’t get this..please help!

Maslowich

Answer:

OPTION 1

Step-by-step explanation:

You just basically plug in x and y values in all the equations and check if you get the same answer each time.

Option 1 is correct because when you plug in let's say the first coordinates,10 and 4 it does give you 6 which is right.

Or you can test it the other way, just plugging in x values and see if you get the right y value for it shown above in the table.

Hope this helps!

3 0

3 years ago

Can someon help me plis?

PtichkaEL [24]

this one lol

Step-by-step explanation:

because this shape has 12 sides when every other shape has 13

4 0

3 years ago

Read 2 more answers

The U.S. Center for Disease Control reports that the mean life expectancy was 47.6 years for whites born in 1900 and 33.0 years

inn [45]

Answer:

b. The null and alternative hypothesis are:

$H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2\neq 0$

c. Student's t distribution, as it is a two-sample test for the difference between means.

d. Test statistic t = 5.42.

P-value = 0

e. They appear to be significantly different, as the sample data gives strong evidence that the difference is greater than 0.

Step-by-step explanation:

This is a hypothesis test for the difference between populations means.

The claim is that the mean life spans in the county is significantly different for whites and nonwhites.

Then, the null and alternative hypothesis are:

$H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2\neq 0$

The significance level is 0.05.

The sample 1 (white), of size n1=124 has a mean of 45.3 and a standard deviation of 12.7.

The sample 2 (non-white), of size n2=82 has a mean of 34.1 and a standard deviation of 15.6.

The difference between sample means is Md=11.2.

$M_d=M_1-M_2=45.3-34.1=11.2$

The estimated standard error of the difference between means is computed using the formula:

$s_{M_d}=\sqrt{\dfrac{\sigma_1^2}{n_1}+\dfrac{\sigma_2^2}{n_2}}=\sqrt{\dfrac{12.7^2}{124}+\dfrac{15.6^2}{82}}\\\\\\s_{M_d}=\sqrt{1.301+2.968}=\sqrt{4.269}=2.066$

Then, we can calculate the t-statistic as:

$t=\dfrac{M_d-(\mu_1-\mu_2)}{s_{M_d}}=\dfrac{11.2-0}{2.066}=\dfrac{11.2}{2.066}=5.42$

The degrees of freedom for this test are:

df=n_1+n_2-2=124+82-2=204

This test is a two-tailed test, with 204 degrees of freedom and t=5.42, so the P-value for this test is calculated as (using a t-table):

$\text{P-value}=2\cdot P(t>5.42)=0.0000002$

As the P-value (0.0000002) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is enough evidence to support the claim that the mean life spans in the county is significantly different for whites and nonwhites.

4 0

3 years ago

In spring 2014, faculty from the City University of New York (CUNY) reported on a randomized controlled trial they conducted. Th

Tems11 [23]

Answer:

Explanatory variable: Extra support by faculties

Response variable: whether community college students who have assess into elementary algebra could be successful if they were placed directly into college-level statistics.

Confounding Variable: Ability of students to get passing grades.

It is an experiment to check if the hypothesis is true.

Step-by-step explanation:

An explanatory variable is a type of independent variable. An explanatory variable is that variable that explains changes in another variable. It can be anything that might affect the response variable. The explanatory variable is used to predict or explain differences in the response variable. In an experimental or research study, the explanatory variable is the variable that is manipulated by the researcher.

From the information given,

Explanatory variable: Extra support by faculties.

The response variable is also known as the dependent/outcome variable. Here, its value can be predicted or its variation can be explained by the explanatory variable. In an experimental study, this is the outcome that is measured after manipulation of the explanatory variable

From the question above,

Response variable: whether community college students who have assess into elementary algebra could be successful if they were placed directly into college-level statistics.

A confounding variable is that outside influence that changes the effect of a dependent and independent variable. This extraneous influence is often used to influence the outcome of an experimental design. The Confounding Variable in the above is:

Confounding Variable: Ability of students to get passing grades.

It is an experiment to check if the hypothesis is true.

6 0

3 years ago

What is bigger 1/3 or 3/5

raketka [301]

$Method\ 1:$

$\dfrac{1}{3}=\dfrac{1\cdot5}{3\cdot5}=\dfrac{5}{15}\\\\\dfrac{3}{5}=\dfrac{3\cdot3}{5\cdot3}=\dfrac{9}{15}\\\\\dfrac{3}{15} < \dfrac{9}{15}\ therefore\ \dfrac{3}{5}\ is\ bigger$

$Method\ 2:$

$\dfrac{1}{3} < \dfrac{1}{2}=\dfrac{1.5}{3}\\\\\dfrac{3}{5} > \dfrac{1}{2}=\dfrac{2.5}{5}\\\\therefore\ \dfrac{3}{5}\ is\ bigger$

6 0

3 years ago