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Lapatulllka [165]
2 years ago
5

Can someone help me, please!!

Mathematics
1 answer:
love history [14]2 years ago
5 0

Id say its option 3.

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7 x 5e = 105 <br><br><br>plz help ​
Anon25 [30]

e=3.

So this is how I approached this. Since 7 is being multiplied, I divided both sides by 7 so 105/7 = 15. Then it becomes simple as 5e=15. We divide both sides by 5 and get e=3. Tip: just try isolating the variable and then life is much easier.

8 0
3 years ago
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Mr. Rijo bought 49 bags of soil one week and 28 bags of soil the next week. Which expression correctly applies the
earnstyle [38]

Answer:

49 + 28 = 7(7 + 4)

Step-by-step explanation:

49 bags of soil one week

28 bags of soil the next week

49 + 28 bags of soil purchased in total

Find the GCF (Greatest Common Factor) of 49 and 28.

49/7 = 7

28/7 = 4 (GCF is 7 since it is the largest number that can divide both 49 and 28 equally)

Factor out the GCF + rewrite division above (optional for visualization)

49/7 = 7 -> 49 = 7 * 7

28/7 = 4 -> 28 = 7 * 4

49 + 28 = 7(7 + 4)

Let me know if you have any questions!

8 0
2 years ago
A farmer plants 0.6 of a field with peanuts. The field is 5.6 acres in size. How many acres are planted with peanuts?
dsp73

Answer:

3.36 acres

Step-by-step explanation:

4 0
3 years ago
What are the three solids naturally found in the atmosphere? water is one of them?
Free_Kalibri [48]
The answer is dust,salt and ice

three common solids are salt crystals,dust and smoke
And no water is not one!
8 0
3 years ago
A fisheries biologist has been studying horseshoe crabs. She has sampled 100 horseshoe crabs and recorded their weight (in kilog
stellarik [79]

Answer:

C. 98

Step-by-step explanation:

The proposed regression equation is weight = b + width * m

R2 = 0.423

A.) What is the regression equation for this example?

The estimate for the y-intercepts is b= 2.3013 and the estimate for the slope is m= 0.7963

In general, we can symbolize the estimated regression equation as ^Y= b + m*Xi. For this example you have to replace it with the calculated values of the regression coefficients to obtain the estimated regression equation:

^Y= 2.3013 + 0.7963Xi

B.) What is the explanatory, or predictor, variable in this study?

The explanatory or predictor variable is the variable that is suspected to have an effect over the response variable. In this example the predictor variable is:

X: Width of a horseshoe crab (cm)

C.) If the researcher wanted to test whether there is a statistically significant relationship between these two variables, what would the test statistic be? Calculate it from the table above.

To test if the regression is significant, the parameter of study will be the slope of the regression equation, symbolically: β. If the slope is equal to zero "β=0" then there is no linear regression between the response and explanatory variable. If the slope is different from zero "β≠0" then the regression is significant and the explanatory variable affects the response variable.

The hypotheses are:

H₀: β=0

H₁: β≠0

α: 0.05

The value of the statistic under the null hypothesis is t= 8.48

D.) What can we say about the p-value?

This test is two-tailed and so is the p-value, remember that the p-value is the probabulity of obtaining a value as extreme as the value of the statistic under the null hypothesis. The distribution for this test is a t with n-2= 100-2= 98 degrees of freedom. You can calculate the p-value as:

P(t₉₈≤-8.48) + P(t₉₈≥8.48)= P(t₉₈ ≤ -8.48) + (1 - P(t₉₈ < 8.48) ≅ 0.00001

E.) Ultimately, the reason that we find test statistics is so that we can compare them to a null distribution. For regression, that is a t-distribution based on the degrees of freedom. With 98 degrees of freedom (100-2), we can safely say that the critical t (or the confidence multiplier) is what?

As mentioned before, this test is two tailed, meaning that the rejection region is divided in two:

Critical values ± = ± = ± 1.984

This means that you'll reject the null hypothesis when the statistic is t ≤ -1.984 or if the statistic is t ≥ 1.984-

F.) Find the confidence interval for the slope.

Using a 95% confidence level, the interval for the slope is:

[m ± Sm]

[0.7963 ± 1.984 * 0.0939]

[0.61; 0.98]

G.) Is there a statistically significant relationship? Answer with the test statistic and the confidence interval.

Yes, there is a significant relationship between the width and weight of the horseshoe crabs.

Using the critical value approach:

The calculated statistic is 8.48 and the critical value is ± 1.984, since the statistic is greater than the positive critical value, the decision is to reject the null hypothesis.

If you pay attention to the confidence interval, which was made at a confidence level complementary to the significance level of the hypothesis test, this interval [0.61; 0.98] doesn't include the "zero". Since the interval doesn't include the value of the parameter stated in the null hypothesis, you can conclude that this hypothesis is not true and therefore reject it.

4 0
3 years ago
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