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ra1l [238]
3 years ago
7

(3-6)(-14--12)

6)( - 14 - - 12)" alt="(3 - 6)( - 14 - - 12)" align="absmiddle" class="latex-formula">
Mathematics
1 answer:
castortr0y [4]3 years ago
4 0

Answer:


Step-by-step explanation:

(-3)(-14--12)

(-3)(-2)

6


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Round to the nearest ten thousand 13,501
lesya692 [45]

Answer:

10,000

Step-by-step explanation:

13501 is below 1500 so it would round down

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If 3(r+300)=6 then find the value of r+300-2
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Answer:

0

Step-by-step explanation:

3(r+300)=6

Divide each side by 3

3/3(r+300)=6/3

(r+300)=2

Now we want to find

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A certain number line uses 20 spaces between consecutive integers.
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Answer:

Distance between two consecutive tick marks is 0.05 units.

Step-by-step explanation:

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It is given that there are 20 ticks between two consecutive number.

Let n and n+1 be the consecutive number.

Formula:

Distance between two ticks =

\displaystyle\frac{\text{Difeerence between the numbers}}{\text{Number of ticks}}\\\\= \frac{(n+1)-n}{20} = \frac{1}{20} = 0.05

Thus, distance between two consecutive tick marks is 0.05 units.

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A number is 2 tens more than 923
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Consider the following hypothesis test.H0:μ1−μ2=0 Ha:μ1−μ2≠0The following results are for two independent samples taken from the
Julli [10]

Answer:

a) z =\frac{104-106}{\sqrt{\frac{8.4^2}{80} +\frac{7.6^2}{70}}}= -1.53  

b) p_v =2*P(z

c) Since the p value is higher than the significance level provided we have enogh evidence to FAIL to reject the null hypothesis and we can't conclude that the true means are different at 5% of significance

Step-by-step explanation:

Information given

\bar X_{1}= 104 represent the mean for 1

\bar X_{2}= 106 represent the mean for 2

\sigma_{1}= 8.4 represent the population standard deviation for 1

\sigma_{2}= 7.6 represent the population standard deviation for 2

n_{1}=80 sample size for the group 1

n_{2}=70 sample size for the group 2

z would represent the statistic

Hypothesis to test

We want to check if the two means for this case are equal or not, the system of hypothesis would be:

H0:\mu_{1}=\mu_{2}

H1:\mu_{1} \neq \mu_{2}

The statistic would be given by:

z =\frac{\bar X_1-\bar X_2}{\sqrt{\frac{\sigma^2_1^2}{n_1} +\frac{\sigma^2_2^2}{n_2}}}=(1)

Part a

Replacing we got:

z =\frac{104-106}{\sqrt{\frac{8.4^2}{80} +\frac{7.6^2}{70}}}= -1.53

Part b

The p value would be given by this probability:

p_v =2*P(z

Part c

Since the p value is higher than the significance level provided we have enogh evidence to FAIL to reject the null hypothesis and we can't conclude that the true means are different at 5% of significance

6 0
3 years ago
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