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3 years ago

-7(1-10) Giving brainlist out again

Mathematics

1 answer:

belka [17]3 years ago

8 0

Answer:

Step-by-step explanation:

-7(1-10)

10-1=9

9 – -7=2

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After comparing response times between the audio and picture portions of the MIT test, the t-test resulted in a t-value of 2.97.

Veronika [31]

Answer:

e. reject the null hypothesis the p value is less than 0.05. therefore the difference is significant.

Step-by-step explanation:

given that after comparing response times between the audio and picture portions of the MIT test, the t-test resulted in a t-value of 2.97.

test statistic t = 2.97

Sample size n =250

Critical value of t at 95% is 1.96

We find that test statistic absolute value is greater than 1.96

So p value would be less than 0.05

This implies that null hypothesis stands in the rejected region.

So reject null hypothesis would be correct conclusion. Sample size cannot be said to be small as more than 30 itself is a good sample size.

e. reject the null hypothesis the p value is less than 0.05. therefore the difference is significant.

5 0

3 years ago

70,000 ones equal how many thousands?

Murrr4er [49]

70,000 ones is equal to 70,000/1000 thousands

70,000 ones = 70 thousands

8 0

3 years ago

Read 2 more answers

#10 i The table shows the admission costs (in dollars) and the average number of daily visitors at an amusement park each the pa

lions [1.4K]

The line of best fit is a straight line that can be used to predict the

average daily attendance for a given admission cost.

Correct responses:

The equation of best fit is; $\underline{ \hat Y = 1,042 - 4.9 \cdot X_i}$

The correlation coefficient is; r ≈<u> -0.969</u>

<h3>Methods by which the line of best fit is found</h3>

The given data is presented in the following tabular format;

$\begin{tabular}{|c|c|c|c|c|c|c|c|c|}Cost, (dollars), x&20&21&22&24&25&27&28&30\\Daily attendance, y&940&935&940&925&920&905&910&890\end{array}\right]$

The equation of the line of best fit is given by the regression line

equation as follows;

$\hat Y = \mathbf{b_0 + b_1 \cdot X_i}$

Where;

$\hat Y$ = Predicted value of the<em> i</em>th observation

b₀ = Estimated regression equation intercept

b₁ = The estimate of the slope regression equation

$X_i$ = The <em>i</em>th observed value

$b_1 = \mathbf{\dfrac{\sum (X - \overline X) \cdot (Y - \overline Y) }{\sum \left(X - \overline X \right)^2}}$

$\overline X$ = 24.625

$\overline Y$ = 960.625

$\mathbf{\sum(X - \overline X) \cdot (Y - \overline Y)} = -433.125$

$\mathbf{\sum(X - \overline X)^2} = 87.875$

Therefore;

$b_1 = \mathbf{\dfrac{-433.125}{87.875}} \approx -4.9289$

Therefore;

The slope given to the nearest tenth is b₁ ≈ -4.9

$b_0 = \mathbf{\dfrac{\left(\sum Y \right) \cdot \left(\sum X^2 \right) - \left(\sum X \right) \cdot \left(\sum X \cdot Y\right)} {n \cdot \left(\sum X^2\right) - \left(\sum X \right)^2}}$

By using MS Excel, we have;

n = 8

∑X = 197

∑Y = 7365

∑X² = 4939

∑Y² = 6782675

∑X·Y = 180930

(∑X)² = 38809

Therefore;

$b_0 = \dfrac{7365 \times 4939-197 \times 180930}{8 \times 4939 - 38809} \approx \mathbf{1041.9986}$

The y-intercept given to the nearest tenth is b₀ ≈ 1,042

The equation of the line of best fit is therefore;

$\underline{\hat Y = 1042 - 4.9 \cdot X_i}$

The correlation coefficient is given by the formula;

$\displaystyle r = \mathbf{\dfrac{\sum \left(X_i - \overline X) \cdot \left(Y - \overline Y \right)}{ \sqrt{\sum \left(X_i - \overline X \right)^2 \cdot \sum \left(Y_i - \overline Y \right)^2} }}$