Someone help me with this! C;

The missing measures on the right triangle are given as follows:

The three trigonometric ratios are the sine, the cosine and the tangent of an angle, and they are obtained according to the rules presented as follows:

Applying the Pythagorean Theorem, the hypotenuse BC is obtained as follows:

(BC)² = 21² + 35²

[tex]BC = \sqrt{21^2 + 35^2}[/tex]

BC = 40.8.

The side of length 21 is opposite to the angle C, hence it's measure is given as follows:

sin(C) = 21/40.8

C = arcsin(21/40.8)

C = 31º.

The non-right angles in a right triangle are complementary, hence the measure of angle B is given as follows:

m < B + 31 = 90

m < B = 59º.

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The triangles are similar by the Angle-Angle (AA) postulate.

Given that two triangles shared vertical angle and the sides opposite the vertical angles are parallel.

We need to determine if the triangles are similar or not,

The Angle-Angle postulate states that if two angles of one triangle are congruent to two angles of another triangle, then the triangles are similar. In this case, the shared vertical angle and the fact that the sides opposite the vertical angles are parallel establish the necessary conditions for the Angle-Angle postulate.

Therefore, we can conclude that the triangles are similar based on the Angle-Angle postulate.

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To meet this requirement, the length of the `left_on` parameter should be equal to the number of levels in the index of the "right" DataFrame. This ensures that the merging is done correctly, aligning the specified columns in the "left" DataFrame with the corresponding levels in the "right" DataFrame's index.

When you're using the pandas merge() function to combine two dataframes, one of the parameters you'll need to specify is "left_on". This is the name or list of names of the columns in the left dataframe that you want to use to merge the two dataframes.

However, when you're merging dataframes, you also need to specify the index of the "right" dataframe. This index can have one or more levels, depending on the data.
e right dataframe. For example, let's say you have two dataframes: "df1" and "df2". "df1" has two columns named "key1" and "key2", while "df2" has a multi-level index with two levels named "level1" and "level2". If you want to merge these two dataframes based on the values in "key1" and "key2" from "df1", you would set "left_on=['key1', 'key2']". Since "df2" has a two-level index, the length of "left_on" must be 2.

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Answer:

[tex]52^{\circ}[/tex]

Step-by-step explanation:

Explanation is attached below.

The area between the graphs is A = e - 1 - sin(1)

To find the exact value of the area between the graphs of y = cos(x) and  [tex]y = e^x[/tex]for 0 ≤ x ≤ 1, we need to calculate the definite integral of the difference between the two functions over the given interval.

Let's denote the area as A. Then we have:

A = ∫[0, 1] ([tex]e^x[/tex] - cos(x)) dx

To find the exact value of this integral, we can integrate each term separately:

A = ∫[0, 1] [tex]e^x[/tex] dx - ∫[0, 1] cos(x) dx

Integrating [tex]e^x[/tex] gives us:

A = [tex]e^x[/tex] |[0, 1] - ∫[0, 1] cos(x) dx

The antiderivative of cos(x) is sin(x), so we have:

A = [tex]e^x[/tex] |[0, 1] - sin(x) |[0, 1]

Evaluating the expressions at the upper and lower limits, we get:

A = [tex]e^1 - e^0[/tex] - sin(1) + sin(0)

Simplifying further:

A = e - 1 - sin(1)

This is the exact value of the area between the graphs of y = cos(x) and y = [tex]e^x[/tex] for 0 ≤ x ≤ 1.

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Stephen's average speed for the round trip was 48 mph.

To find Stephen's average speed, we can use the formula:

Average Speed = Total Distance / Total Time

Let's assume the distance from Stephen's house to his aunt's house is 'd' miles.

On the way to his aunt's house, Stephen traveled at a speed of 60 mph. So the time taken for this leg of the trip is given by:

Time = Distance / Speed = d / 60

On the return trip, Stephen traveled at a speed of 40 mph. So the time taken for this leg of the trip is:

Time = Distance / Speed = d / 40

The total time for the round trip is the sum of the times for the outward and return trips:

Total Time = d / 60 + d / 40

To find the average speed, we divide the total distance by the total time:

Average Speed = Total Distance / Total Time

The total distance for the round trip is 2d (since it's the same roadway for both trips).

Average Speed = 2d / (d / 60 + d / 40)

Simplifying this expression, we get:

Average Speed = 2d / ((3d + 2d) / 120) = 2d / (5d / 120) = 2d * 120 / 5d = 240 / 5 = 48 mph

Therefore, Stephen's average speed for the round trip was 48 mph.

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The resulting vector will be shorter than the original vector.

From the question, we have the following parameters that can be used in our computation:

Multiplying the vector by a scale factor of Negative one-half.

This means that

Scale = -1/2

When a vector is multiplied by a scale whose absolute value is less than 1

The new vector will be shorter

using the above as a guide, we have the following:

The resulting vector will be shorter than the original vector.

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In a test of hypothesis the p-value was 0.24. If the level of significance is 10 %. The potential type of statistical error is a) Type II error.

In hypothesis testing, Type I error occurs when the null hypothesis is incorrectly rejected, while Type II error occurs when the null hypothesis is incorrectly accepted. The p-value of 0.24 is greater than the significance level of 0.10, which means there is not enough evidence to reject the null hypothesis.

Therefore, the potential error would be a Type II error, as the null hypothesis may be true but erroneously accepted. Therefore the option a is correct answer of the question.

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The equivalent matrix of [tex]\left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&2^2\\\sqrt{25&4&3^2\end{array}\right][/tex] is [tex]\left[\begin{array}{ccc}2&2&2\\1&25&4\\5&4&9\end{array}\right][/tex]

From the question, we have the following parameters that can be used in our computation:

[tex]\left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&2^2\\\sqrt{25&4&3^2\end{array}\right][/tex]

Evaluate the exponents in the matrix

So, we have the following representation

[tex]\left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&2^2\\\sqrt{25&4&3^2\end{array}\right] = \left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&4\\\sqrt{25&4&9\end{array}\right][/tex]

Evaluate the square roots in the matrix

So, we have the following representation

[tex]\left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&2^2\\\sqrt{25&4&3^2\end{array}\right] = \left[\begin{array}{ccc}2&2&2\\1&25&4\\5&4&9\end{array}\right][/tex]

This means that the equivalent matrix of [tex]\left[\begin{array}{ccc}2&\sqrt 4&2\\1&25&2^2\\\sqrt{25&4&3^2\end{array}\right][/tex] is [tex]\left[\begin{array}{ccc}2&2&2\\1&25&4\\5&4&9\end{array}\right][/tex]

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The given quadrilateral is a trapezoid, because the figure has exactly one pair of parallel sides.

We have,

A quadrilateral is a closed shape and a type of polygon that has four sides, four vertices and four angles. It is formed by joining four non-collinear points.

Given is a figure of a quadrilateral, we need to identify what is the type of the quadrilateral,

The options are given about parallelograms and trapezoids,

So, it can not be a parallelogram because, in parallelograms both the pairs of opposite sides are congruent and equal, but here sides are uneven, so it is not a parallelogram.

Now, according to the definition of a trapezoid, it is a type of quadrilateral which have exactly one pair of parallel sides,

In the figure also the quadrilateral is having exactly one side parallel.

Hence, the given quadrilateral is a trapezoid, because the figure has exactly one pair of parallel sides.

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complete question:

Which name accurately describes the figure shown below and why?

help quick

A. parallelogram, because the figure has two pairs of parallel sides

B. parallelogram, because the figure has exactly one pair of parallel sides

C. trapezoid, because the figure has two pairs of parallel sides

D. trapezoid, because the figure has exactly one pair of parallel sides

Hello !

[tex]13 - x = 21\\\\13 - x - 13 = 21 - 13\\\\-x = 8\\\\\boxed{x = -8}[/tex]

Hello !

Answer:

[tex]\boxed{\sf x=-8}[/tex]

Step-by-step explanation:

We're looking for the value of x that satisfies the following equation :

[tex]\sf 13-x=21[/tex]

Let's isolate x in the equation.

First, substract 13 from both sides :

[tex]\sf 13-x-13=21-13\\\sf -x=8[/tex]

Now let's multiply both sides by -1 :

[tex]\sf -1\times (-x)=-1\times 8\\\boxed{\sf x=-8}[/tex]

Have a nice day ;)

B, C, E and F are true statements.

A and D aren't.

The sum of the series s = ∑n=4^∞ 1/(n(n−1)) is 1/4.

To write the series s = ∑n=4^∞ 1/(n(n−1)) as a telescoping series, we need to manipulate the terms to cancel each other out and simplify the expression.

We can rewrite the series as:

s = ∑n=4^∞ (1/n - 1/(n-1))

Expanding the summation:

s = (1/4 - 1/3) + (1/5 - 1/4) + (1/6 - 1/5) + ...

Notice that the term -1/(n-1) in each subsequent term cancels out with the 1/n term in the next term, except for the first term (1/4 - 1/3).

We can simplify the expression by canceling out the terms:

s = 1/4 - 1/3 + 1/5 - 1/4 + 1/6 - 1/5 + ...

The consecutive terms cancel out, leaving only the first term:

s = 1/4

Therefore, the sum of the series s = ∑n=4^∞ 1/(n(n−1)) is 1/4.

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In the given study comparing the effects of regular-fat cheese to reduced-fat cheese on LDL cholesterol levels, the dependent variable(s) refers to the outcome(s) that are being measured or observed. In this case, the dependent variable in this study is: b. LDL levels

The dependent variable is the variable that is measured or observed to assess the effect of the independent variable(s). In this case, the study is comparing the effects of regular-fat cheese and reduced-fat cheese on LDL cholesterol levels.

LDL cholesterol levels are the outcome being measured to determine the impact of the different types of cheese on cholesterol. Therefore, option b, LDL levels, is the dependent variable in this study. Options a (regular fat cheese) and c (reduced fat cheese) are not the dependent variables but rather the independent variables, as they are the different conditions being compared to assess their effect on LDL levels.

Option d (both a and b) and option e (both b and c) are incorrect because regular-fat cheese (option a) is an independent variable, not a dependent variable.

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The surface area of the composite figure is 416 square cm because the composite figure is made up of two figures.

Since, A rectangular prism is defined as the six-faced shape, a type of hexahedron in geometry.

It is a three-dimensional shape. It is also called a cuboid.

We have a composite figure shown in the picture.

As we can see in the picture the composite figure is made up of two figures.

The first one is a rectangular prism

Second one is a triangular prism.

The surface area of the composite figure:

= area of the two triangle shapes + area of the two rectangles in triangular prism + surface area of the rectangular prism - (12x5)

= 2(1/2)12x10 + 2(10x5) + 2(4x5 + 12x5 + 12x4) - 12x5

= 120 + 2(50) + 2(20 + 60 + 48) - 60

= 120 + 100 + 2(128) - 60

= 120 + 100 + 256 - 60

= 416 square cm

Thus, the surface area of the composite figure is 416 square cm because the composite figure is made up of two figures.

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Answer:

7) y = -6x^2 + 60x

a. -6x^2 + 60x = 0

-6x(x - 10) = 0

x = 10 seconds

b. The highest point occurs at 5 seconds.

-6(5^2) + 60(5) = -150 + 300 = 150 feet

c. -6x^2 + 60x = 96

-6x^2 + 60x - 96 = 0

6x^2 - 60x + 96 = 0

x^2 - 10x + 16 = 0

(x - 2)(x - 8) = 0

x = 2 seconds, 8 seconds

8) y = -3x^2 + 18x

a. -3x^2 + 18x = 0

-3x(x - 6) = 0

x = 6 seconds

b. The highest point occurs at 3 seconds.

-3(3^2) + 18(3) = -27 + 54 = 27 feet

c. -3x^2 + 18x = 24

-3x^2 + 18x - 24 = 0

3x^2 - 18x + 24 = 0

x^2 - 6x + 8 = 0

(x - 2)(x - 4) = 0

x = 2 seconds, 4 seconds

The length of the other diagonal of the kite which has an area of 78[tex]in^{2}[/tex] and the length of one diagonal 12 inches is 13 inches.

To find the length of the other diagonal of the kite, we can use the formula for the area of a kite, which is given by:

Area = (1/2) * d1 * d2

Where:

Area = 78 in² (given)

d1 = length of one diagonal = 12 inches (given)

d2 = length of the other diagonal (to be determined)

Plugging in the given values, we have:

78 in² = (1/2) * 12 in * d2

To solve for d2, we can rearrange the equation:

d2 = (2 * 78 in²) / 12 in

Simplifying further:

d2 = 156 in² / 12 in

d2 = 13 in

Therefore, the length of the other diagonal of the kite is 13 inches.

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The dividend on an 8 percent preferred stock that currently sells for $45 and has a face value of $50 per share is $4.00. The correct option is a.

The dividend on a preferred stock can be calculated using the formula: Dividend = Preferred Stock Price × Preferred Stock Dividend Rate. In this case, the preferred stock price is $45, and the preferred stock dividend rate is 8 percent. To calculate the dividend, we multiply $45 by 8 percent (0.08): $45 × 0.08 = $3.60.

However, it's important to note that preferred stock dividends are typically calculated based on the face value of the stock rather than the market price. The face value represents the original value of the stock and is often $100 or $50 per share. In this case, the face value is $50 per share. To adjust for the face value, we divide the calculated dividend by the market price and multiply it by the face value: ($3.60 ÷ $45) × $50 = $4.00. Therefore, the dividend on an 8 percent preferred stock that currently sells for $45 and has a face value of $50 per share is $4.00. The correct answer is A. $4.00.

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True. The correlation coefficient (r) must also be positive, indicating a strong positive linear relationship between the two variables.

The correlation coefficient (r) measures the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where a value of -1 indicates a perfectly negative linear relationship, a value of 1 indicates a perfectly positive linear relationship, and a value of 0 indicates no linear relationship.  If the slope (b) of ŷ is positive, it means that as the independent variable increases, the dependent variable also increases.

In addition to the above explanation, it is important to note that while a positive slope (b) of ŷ indicates a positive linear relationship between two variables, it does not necessarily mean that the correlation coefficient (r) will always be positive. For example, if there is a weak positive linear relationship between two variables, the correlation coefficient (r) may still be positive but not as strong as if there was a strong positive linear relationship. Similarly, there may be situations where the correlation coefficient (r) is positive but the slope (b) of ŷ is not positive, such as in a curvilinear relationship where the relationship between the two variables is not linear.

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Based on the sample data and the hypothesis test, there is sufficient evidence to support the claim that the population mean μ is greater than 29 at the significance level of 0.05.

What is the mean and standard deviation?

The standard deviation is a summary measure of the differences of each observation from the mean. If the differences themselves were added up, the positive would exactly balance the negative and so their sum would be zero. Consequently, the squares of the differences are added.

To test the claim about the population mean μ at the level of significance α, we can perform a one-sample t-test.

Given:

Claim: μ > 29 (right-tailed test)

α = 0.05

σ = 1.2 (population standard deviation)

Sample statistics: x = 29.3 (sample mean), n = 50 (sample size)

We can follow these steps to conduct the hypothesis test:

Step 1: Formulate the null and alternative hypotheses.

The null hypothesis (H₀): μ ≤ 29

The alternative hypothesis (Hₐ): μ > 29

Step 2: Determine the significance level.

The significance level α is given as 0.05. This represents the maximum probability of rejecting the null hypothesis when it is actually true.

Step 3: Calculate the test statistic.

For a one-sample t-test, the test statistic is given by:

t = (x - μ) / (σ / √(n))

In this case, x = 29.3, μ = 29, σ = 1.2, and n = 50. Plugging in the values, we get:

t = (29.3 - 29) / (1.2 / √(50))

= 0.3 / (1.2 / 7.07)

= 0.3 / 0.17

≈ 1.76

Step 4: Determine the critical value.

Since it is a right-tailed test, we need to find the critical value that corresponds to the given significance level α and the degrees of freedom (df = n - 1).

Looking up the critical value in a t-table with df = 49 and α = 0.05, we find the critical value to be approximately 1.684.

Step 5: Make a decision and interpret the results.

If the test statistic (t-value) is greater than the critical value, we reject the null hypothesis; otherwise, we fail to reject the null hypothesis.

In this case, the calculated t-value is approximately 1.76, which is greater than the critical value of 1.684. Therefore, we reject the null hypothesis.

hence, Based on the sample data and the hypothesis test, there is sufficient evidence to support the claim that the population mean μ is greater than 29 at the significance level of 0.05.

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Using the first part of the fundamental theorem of calculus, the derivative of the given function y = ∫ 2 3x+7 t/1+t^3 dt is y' = (3x+7)/(1+(3x+7)^3).

The first part of the fundamental theorem of calculus states that if a function f(x) is continuous on the closed interval [a, b], and F(x) is an antiderivative of f(x) on that interval, then the definite integral of f(x) from a to x can be expressed as F(x) - F(a).

Using this theorem, we can find the derivative of the given function y as follows:

y = ∫ 2 3x+7 t/1+t^3 dt

Taking the derivative of both sides with respect to x, we get:

y' = d/dx ( ∫ 2 3x+7 t/1+t^3 dt )

Using the chain rule, we have:

y' = (d/dx) (3x+7) * (∫ 2 3x+7 t/1+t^3 dt )

y' = 3 * (∫ 2 3x+7 t/1+t^3 dt )

Now, we need to evaluate the integral of t/(1+t^3) with respect to t. We can do this using the substitution u = 1 + t^3, du = 3t^2 dt, and rewriting the integral as:

∫ 1/(u) du/3 = (1/3) * ln|u| + C = (1/3) * ln|1+t^3| + C

where C is the constant of integration.

Substituting this back into the expression for y', we get:

y' = 3 * (1/3) * ln|1+(3x+7)^3| + C

Simplifying this expression, we get:

y' = (3x+7)/(1+(3x+7)^3) + C

where C is the constant of integration.

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The initial value problem x^2y'' - 2xy' + 2y = xln(x), with y(1) = 1 and y'(1) = 0, is best described as a second-order, inhomogeneous, variable-coefficient differential equation with given initial conditions.

The initial value problem x^2y''-2xy' + 2y=xlnx, y(1)=1, y'(1)=0 is a second-order linear differential equation with variable coefficients. The method of undetermined coefficients can be used to find a particular solution for the nonhomogeneous term xlnx, and the general solution can be obtained by adding the complementary solution, which is the solution to the associated homogeneous equation x^2y''-2xy' + 2y=0, to the particular solution. The initial conditions y(1)=1 and y'(1)=0 can then be used to determine the constants in the general solution.

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The number of possible king-queen pairs can be determined by multiplying the number of candidates for king by the number of candidates for queen.

To calculate the number of king-queen pairs, we multiply the number of candidates for king by the number of candidates for queen. In this case, there are four candidates for homecoming queen and three candidates for king. Therefore, the total number of king-queen pairs would be 4 multiplied by 3, which equals 12.

Each candidate for king can be paired with each candidate for queen, resulting in multiple possible combinations. By multiplying the number of candidates for each position, we account for all possible pairings. In this scenario, there are three potential kings and four potential queens. For each king, there are four possible queens he can be paired with. Since there are three kings, we multiply 3 by 4 to get the total number of 12 king-queen pairs.

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This power series is centered at 0 and represents the function h(x) = −2x^2 − 1.

To find the power series for h(x) = −2x^2 − 1, we can start with the power series expansion for 1/(1 − x), which is given by ∑ (-1)^n * x^n for |x| < 1. We want to manipulate this series to obtain the desired function h(x).

First, we multiply the power series by x^2 to obtain ∑ (-1)^n * x^(n+2). This shifts the powers of x by 2, resulting in x^2, x^3, x^4, and so on.

Next, we multiply the entire series by 2 to obtain ∑ (-1)^n * 2x^(n+2). This scales the coefficients by a factor of 2.

Finally, we subtract 1 from the series to obtain ∑ (-1)^n * 2x^(n+2) - 1. This subtracts 1 from each term of the series.

Therefore, the power series representation of h(x) is ∑ (-1)^n * 2x^(n+2) - 1. This power series is centered at 0 and represents the function h(x) = −2x^2 − 1.

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In this solution, we assume that the given sides of ∆ABC and ∆DEF correspond to each other. So, the side DE is equal to 6 cm.

Since ∆ABC ~ ∆DEF, the corresponding sides of the triangles are proportional to each other, from that the following proportion can be done:

AB/DE = BC/EF

By substituting the given values, we get:

16/DE = √(64/9)

To simplify the equation, we have to square both the sides:

(16/DE)² = 64/9

By Cross-multiplying, we get:

256 = 64(DE)²/9

By simplifying further, we have:

(DE)² = (256 × 9)/64

(DE)² = 36

By taking the square root of both sides, we get:

DE = √36

DE = 6 cm

Therefore, the DE is equal to 6 cm.

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the area of the region between the graph of y = 64 − x^3 and the x-axis over the interval [2, 4] is 68 square units.

What is a Graph?

A graph is a visual representation of the relationship between two or more variables on the axes.

To find the area of the region between the graph of the function y = 64 − x^3 and the x-axis over the interval [2, 4], we can use the limit process by approximating the area using rectangles and taking the limit as the width of the rectangles approaches zero.

The first step is to divide the interval [2, 4] into smaller subintervals. Let's choose n subintervals, each with a width of Δx = (4 - 2)/n. This will give us n+1 points: x0 = 2, x1, x2, ..., xn-1, xn = 4.

Within each subinterval, we can choose a representative point, xi*, to evaluate the function y = 64 − x^3. The height of the rectangle corresponding to the ith subinterval will then be the function value at that representative point, which is y(xi*).

The area of the ith rectangle is given by A_i = y(xi*) * Δx.

To find the total area, we sum up the areas of all the rectangles:

A_total = A_1 + A_2 + ... + A_n.

Using the limit process, we can find the area by taking the limit as n approaches infinity:

A_total = lim(n→∞) [A_1 + A_2 + ... + A_n].

To evaluate this limit, we need to express it as a definite integral. Recall that the definite integral of a function f(x) over an interval [a, b] is given by:

∫[a,b] f(x) dx.

In our case, the definite integral that represents the area can be written as:

A_total = ∫[2,4] (64 - x^3) dx.

To compute this integral, we can use standard techniques for integration. Integrating the function 64 - x^3 gives us:

A_total = [64x - (x^4)/4] evaluated from x = 2 to x = 4.

Plugging in the limits, we have:

A_total = [64(4) - (4^4)/4] - [64(2) - (2^4)/4].

Simplifying the expression, we get:

A_total = [256 - 64] - [128 - 4].

Calculating further, we find:

A_total = 192 - 124.

Therefore, the area of the region between the graph of y = 64 − x^3 and the x-axis over the interval [2, 4] is 68 square units.

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The distance of the boat from tower A would be =52.1ft.

To calculate the distance of the boat from Tower A the sine rule needs to be obeyed. That is;

a/sinA = b/sinB

where;

a = 100ft

A = 180-(68+31)

= 180-99= 81°

b = d

B = 31°

100/sin81° = d/sin31

make d the subject of formula;

d = 100×0.5150 /0.9877

= 51.5/0.9877

= 52.1ft

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The linear regression to find a function that fits the given coordinate points is y=1/2 x-3.

The given coordinate points are (-2, -4) and (8, 1).

Here, slope = (1+4)/(8+2)

= 5/10

= 1/2

Substitute m= 1/2 and (x, y)=(-2, -4) in y=mx+c, we get

-4 =1/2 (-2) +c

-4 =-1+c

c=-3

So, the equation of a line is y=1/2 x-3

Therefore, the linear regression to find a function that fits the given coordinate points is y=1/2 x-3.

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The line can not be line of best fit because it's not closest to lost of the point.

A line of best fit is a straight line that minimizes the distance between it and some data. It is an output of regression analysis and can be used as a prediction tool for indicators and price movements.

Line of best fit must pass through as many as possible points on the graph. Looking at the line above is on the graph but doesn't not pass through most of the points.

The points are actually representing a value and the line must also represent the value.

Therefore the line above is not a line of best fit

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Answer:

C) It cannot be the line of best fit because it is not closest to most of the points.

Step-by-step explanation:

A scatter plot is a graphical representation of a dataset in which individual data points are plotted as dots on a two-dimensional coordinate system. It is used to visually examine the relationship between two variables and identify patterns or trends in the data.

The line of best fit is a straight line that represents the general trend or pattern in a scatter plot, and minimizes the overall distance between the line and the data points.

To determine if a line on a scatter plot is the line of best fit, you can assess its alignment with the data points. The line of best fit should pass as close as possible to the majority of the data points, minimizing the overall distance between the line and the points.

From observation of the given scatter plot, the line does show a positive association, but it cannot be the line of best fit because it is not closest to most of the points.

Note: The correct line of best fit is shown in red on the attached diagram.