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Dima020 [189]
3 years ago
14

Emily's account balance this Monday is -$8.35 . Her account balance last Monday was $15.75. Which statement explains how to find

the change in Emily's account balance from last Monday to this Monday ? Answer Choices Add this Monday's account balance to last Monday's account balance to find that the change in the balance is $7.40. Subtract last Monday's account balance from this Monday's account balance to find that the change in the balance is $24.10. Subtract last Monday's account balance from this Monday's account balance to find that the change in the balance is -$24.10 . Add last Monday's account balance to this Monday's account balance to find that the change in the balance is -$7.40 . Next Question
Mathematics
1 answer:
Yanka [14]3 years ago
8 0
The correct answer to determine the change in he account is by:

C. Subtracting last Monday's account balance from this Monday's account balance to find that the change in the balance is -$24.10.

Hope This helped :)
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A local car dealer claims that 25% of all cars in San Francisco are blue. You take a random sample of 600 cars in San Francisco
sammy [17]

Answer:

No, we can't reject the dealer's claim with a significance level of 0.05.

Step-by-step explanation:

We are given that a local car dealer claims that 25% of all cars in San Francisco are blue.

You take a random sample of 600 cars in San Francisco and find that 141 are blue.

<u><em>Let p = proportion of all cars in San Francisco who are blue</em></u>

SO, Null Hypothesis, H_0 : p = 25%   {means that 25% of all cars in San Francisco are blue}

Alternate Hypothesis, H_A : p \neq 25%   {means that % of all cars in San Francisco who are blue is different from 25%}

The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;

                                  T.S.  = \frac{\hat p-p}{{\sqrt{\frac{\hat p(1-\hat p)}{n} } } } }  ~ N(0,1)

where, \hat p = sample proportion of 600 cars in San Francisco who are blue =   \frac{141}{600} = 0.235

            n = sample of cars = 600

So, <u><em>test statistics</em></u>  =  \frac{0.235-0.25}{{\sqrt{\frac{0.235(1-0.235)}{600} } } } }

                               =  -0.866

<em>Now at 0.05 significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics lies within the range of critical values of z so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which we fail to reject our null hypothesis.</em>

Therefore, we conclude that 25% of all cars in San Francisco are blue which means the dealer's claim was correct.

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Step-by-step explanation:

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