Y=1/3x-3 and y=-x+1 what the answer pls i really need this

The given expression is

Replacing the given values, we have

The integer that represents this change is -5.

We have,

The change in temperature is represented by the difference between the temperature before and after the storm.

In this case,

The temperature dropped, which means it decreased.

The integer that represents the change in temperature is negative because it indicates a decrease or a loss.

In particular,

The integer that represents a decrease of 5 degrees is -5.

Therefore, if the temperature before the storm was, for example, 20 degrees, the temperature after the storm would be 20 - 5 = 15 degrees, which is 5 degrees lower.

Thus,

The integer that represents this change is -5.

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Answer:

You subtract

Step-by-step explanation:

Given

Borrowing Word Problem

Required

Do you add or subtract?

Take the following illustration as a point of reference:

You have 5 pens. Your friend borrowed 2 pens. How many pens do you have left?

From above:

Initially, you have 5

you lend your friend 2

Then, you have: (5 - 2) left

i.e. 3 pens left

In conclusion, you have to subtract

(a) Option A, if its value is a large positive number, statistic A x2 provides strong evidence for the alternative hypothesis.

(b) Option B, the null hypothesis that gender is not related to personal goals and the alternative hypothesis that gender is related to personal goals.

(c) Option B, the variables considered in the chi-square test for the evaluation of contingency table B are categorical variables.

(a) If the x2 statistic is a large positive number, it provides strong evidence for the alternative hypothesis. The x2 statistic is used in hypothesis testing to determine if there is a significant difference between observed and expected frequencies. Large positive values ​​indicate that the observed frequency is significantly different from the expected frequency, supporting the alternative hypothesis.

(b) The hypotheses tested in the chi-square test for the contingency table are the null hypothesis that gender is not related to personal goals and the alternative hypothesis that gender is related to personal goals. personal goals. This test determines whether there is a significant relationship between two categorical variables.

(c) The variables considered in the chi-square test used to evaluate the contingency table are categorical variables. These variables cannot be assumed to be mean or normally distributed. The chi-square test is used to analyze the relationship between two or more categorical variables, where each variable has a discrete set of categories.

Complete Question:

For each problem, select the best response (a) A x2 statistic provides strong evidence in favor of the alternative hypothesis if its value is A. a large positive number. OB. exactly 1.96 c. a large negative number. D. close to o E. close to 1. (b) A study was performed to examine the personal goals of children in elementary school. A random sample of students was selected and the sample was given a questionnaire regarding achieving personal goals. They were asked what they would most like to do at school: make good grades, be good at sports, or be popular. Each student's sex (boy or girl) was also recorded. If a contingency table for the data is evaluated with a chi-squared test, what are the hypotheses being tested? A. The null hypothesis that boys are more likely than girls to desire good grades vs. the alternative that girls are more likely than boys to desire good grades. OB. The null hypothesis that sex and personal goals are not related vs. the alternative hypothesis that sex and personal goals are related. C. The null hypothesis that there is no relationship between personal goals and sex vs. the alternative hypothesis that there is a positive, linear relationship. OD. The null hypothesis that the mean personal goal is the same for boys and girls vs. the alternative hypothesis is that the means differ. O E. None of the above. (C) The variables considered in a chi-squared test used to evaluate a contingency table A. are normally distributed. B. are categorical. C. can be averaged. OD. have small standard deviations. E. have rounding errors.

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A: The probability that the player gets a move on 3 is 3:42  that is 1:14.

To get into this solution , we first determine all the possible outcomes.

With one dice there are 6 possible outcomes .

With two dice there are 36 possible outcomes because of the combination of the 6 outcomes from each die.

This means there are 36 + 6 = 42 total possible outcomes.

Probability of getting 3 when  one dice is rolled - 1:6.

Probability of getting 3 in two dice is rolled-

There are two possible combinations that is - [(1,2) , (2,1)].

This means there are total of 3 outcomes out of 42 possible outcomes.

Hence the probability that the player gets a move on 3 is 1:14.

B: For a roll(sum) between 5 and 6, a biased coin would give the player an advantage.

A biased coin would give the player an advantage because the player can select one die and improve their odds of getting a 5 or a 6 , which is less likely when rolling two dice.

If the biased coin allows the player to choose two die, the odds of getting a 5 or a 6 is 1:4, a simplification of 9 desired outcomes out of a possible 36.

When rolling two dice , there are 36 possible combinations. The combinations that can result in total of 5 or 6 are [(1,4) , (4,1) , (2,3) , (3,2) , (1,5) , (5,1) , (2,4) , (4,2) , (3,3)].

As the player would want to have a better chance of getting a 5 or a 6, they would want to roll one die.

Knowing the outcome of a biased coin would allow them to choose the side that results in rolling one die rather than two.

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Answer:

I did not graph the constant of proportionality.  It is at point (1, 1/2)

Step-by-step explanation:

See below

Answer:

Lineal.

Step-by-step explanation:

To determine if the sequence 4,10,20,34,52 ....... is a linear model, a quadratic model or a cubic model, the following mathematical logical reasoning must be carried out:

4 to 10 = +6

10 to 20 = +10

20 to 34 = +14

34 to 52 = +18

Thus, we can see at a glance that the sequence increases 4 numbers in each digit, adding first 6, then 10, then 14 and so on, with which the next numbers in that sequence should be 74 (+22), 100 ( +26), 130 (+30), 164 (+34), and so on.

Therefore, since there is no quadratic or cubic relationship, the sequence is linear.

Answer:

Each pound equals $.50.

Step-by-step explanation:

3 divided by 6 equals .50.

The values of angles for the intervals given are obtained as 135°,  405° and -135° respectively.

The trigonometric ratios are defined for a right angled triangle.

The example of these ratios are sin, cos, tan, cosec, sec and cot.

The trigonometric ratios are useful in determining the heights and distances of the large objects.

The given trigonometric equation is sin(θ) = √2/2.

It can be written as,

sin(θ) = √2/2

⇒ sin(θ) = 1/√2

⇒ θ = 45°

(a) The value of the angle in interval 90° < θ < 270° is given as,

⇒ 180°- θ = 180° - 45° = 135°

(b)  The value of the angle in interval 270° < θ < 450° is given as,

⇒ 360°+ θ = 360°+ 45° = 405°

(c) The value of the angle in interval -270° < θ < -90° is given as,

⇒ -180° + θ = -180° + 45° = -135°

Hence, the required values of angles for the given interval are 135°,  405° and -135° respectively.

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The result of the lines after the translation is given as follows:

They do not intersect.

A translation happens when either a figure or a function is moved horizontally or vertically on the coordinate plane.

The vector notation is given as follows:

(g,h).

The meaning is given as follows:

The vector for this problem is given as follows:

(2,1).

Meaning that the lines are shifted 2 units right and one unit down.

Both lines, that do not intersect, are translated, hence the lines continue not intersecting.

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Answer:

{(2^4) }^2

=16^2

= 256

................

Answer:

256

Step-by-step explanation:

Answer:

30

Step-by-step explanation:

Because if you have 35 ducks and I remove 5 you only have 30

Answer:

30

Step-by-step explanation:

35-5=30

llllllllllllllllllllllllllllll lllll-5

count and there are 30 lines left

The number of ways in which we can make a sitting arrangements to meet the requirement is 1440.

= 5!⋅4⋅3

= 120⋅12

= 1440

Combinations are ways to choose things from a collection where the order of the choices is irrelevant. Let's say we have a trio of numbers: P, Q, and R. Then, combination determines how many ways we can choose two numbers from each group.

It is easy to count the number of combinations in smaller cases, but the likelihood of a set of combinations is also higher in cases with many groups of components or sets. As a result, a formula has been developed to determine the number of items that could be chosen which is nCr.

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Answer:

Remember, the absolute value expression will yield a zero or positive answer which is always greater than a negative number.

Step-by-step explanation:

Hope this helps :)

The probability of a random variable (x) being greater than 1.35, given a mean of 1.2 and a standard deviation of 0.13, is approximately 0.1249 or 12.49%.

To find P(x > 1.35) given a mean (μ) of 1.2 and a standard deviation (σ) of 0.13, we can use the standardized normal distribution table or Z-table.

First, we need to standardize the value 1.35 using the formula:

z = (x - μ) / σ

Plugging in the values, we get:

z = (1.35 - 1.2) / 0.13 = 1.1538

Now, we look up the z-value of 1.1538 in the Z-table. The Z-table provides the area under the standard normal distribution curve to the left of a given z-value. Since we need the probability to the right of 1.35, we subtract the corresponding area from 1.

Using the Z-table, we find that the area to the left of 1.1538 is approximately 0.8751. Therefore, the area to the right of 1.35 is 1 - 0.8751 = 0.1249.

So, P(x > 1.35) is approximately 0.1249 or 12.49%.

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Yes. When a graph has more than one line it is a piece wise graph.

The system with impulse response g(t, t) = e^(-2|t|^-|t|) is not BIBO stable, while the system with impulse response g(t, t) = sin(t)e^(-(-t^2)) is BIBO stable.

To determine if a system is BIBO (Bounded-Input Bounded-Output) stable, we need to analyze the impulse response of the system.

For the first system with impulse response g(t, t) = e^(-2|t|^-|t|), let's examine its behavior. The function e^(-2|t|^-|t|) decays rapidly as |t| increases. However, it does not decay fast enough to satisfy the condition for BIBO stability, which requires the integral of |g(t, t)| over the entire time axis to be finite. Since the integral of e^(-2|t|^-|t|) diverges, the first system is not BIBO stable.

For the second system with impulse response g(t, t) = sin(t)e^(-(-t^2)), the term e^(-(-t^2)) represents a Gaussian function that decays exponentially. The sinusoidal term sin(t) can oscillate, but it is bounded between -1 and 1. As the exponential decay ensures that the impulse response is bounded, the second system is BIBO stable.

In summary, the system with impulse response g(t, t) = e^(-2|t|^-|t|) is not BIBO stable, while the system with impulse response g(t, t) = sin(t)e^(-(-t^2)) is BIBO stable.

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Scoring in the 60th percentile on her math exam means that the student performed better than 60% of other test takers.

Percentile is a measure that indicates the percentage of data points that are below a particular value in a given dataset. In this case, the student's score is in the 60th percentile, which means she scored better than 60% of the other test takers.

Imagine arranging all the scores of the test takers in ascending order. The 60th percentile represents the score that is greater than 60% of the scores below it and less than 40% of the scores above it. It is a way of understanding how a particular score compares to the rest of the scores in the group.

However, it also means that 40% of the test takers scored higher than her.  If the student scored in the 60th percentile, it indicates that she performed relatively well compared to the majority of the test takers.

Percentiles provide a useful way to interpret individual scores in relation to the entire distribution of scores in a dataset.

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In general, observational studies are more problematic than randomized controlled trials because they can produce spurious relationships.

Observational studies rely on the natural variation in exposures and outcomes that occur in the population, without any intervention or manipulation by the researcher.

This can lead to confounding variables, which are factors that are associated with both the exposure and the outcome and can produce a false association between them.

Randomized controlled trials, on the other hand, assign participants to different exposure groups at random, which reduces the risk of confounding and allows for a more accurate assessment of causality.

Therefore, researchers must be cautious when interpreting observational studies and consider the potential for spurious relationships.

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The probability of picking a 4 and then picking a 2 is 1/9

From the question, the given parameters are

Cards = 2, 3 and 4

Also, from the question, we have

The selected card is returned to the pack

So, the probability of selecting a card with number 4 is

P(4) =n(4)/Total

This gives

P(4) = 1/3

Also, the probability of selecting a card with number 2 is

P(2) =n(2)/Total

This gives

P(2) = 1/3

The required probability is

P(4 and 2) = 1/3 * 1/3

Evaluate

P(4 and 2) = 1/9

Hence, the probability is 1/9

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The equation's remaining constant is the answer if the variable term eventually equals zero and the equation can be said to be true.

By isolating the variable on one side of the equation, we can arrive at a numerical value that satisfies the equation. However, in rare circumstances, the variable term may become zero while the equation is being simplified.

When a common factor is eliminated or an expression containing the variable is simplified, this can take place. The equation has a solution, and that solution is the constant value left over if, after removing the variable element, we arrive at a true assertion.

This is due to the equation's ability to be simplified to a declaration of equality between two constants if the variable term is zero. The constant value is the answer to the equation if the aforementioned assertion is accurate.

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Answer:

62.96%

Step-by-step explanation:

do this

51/81 ×100%

Answer:62.953%

Step-by-step explanation:

81 * (%) = 51

% = 51 / 81

% = 62.953

Answer: 1.19

Step-by-step explanation: To convert this mixed number (fraction) to a decimal just follow these two steps:

Step 1: divide numerator (19) by the denominator (100): 19 ÷ 100 = 0.19

Step 2: add this value to the the integer part: 1 + 0.19 = 1.19. So,

1 19/100 = 1.19

Rounded values:

1 19/100 = 1 rounded to 0 decimal places

1 19/100 = 1.2 rounded to 1 decimal place1

Answer:

Area of the parallelogram is approximately 4,456.2 square feet

Step-by-step explanation:

The lengths of the sides of the parallelogram are 65 feet and 87 feet

The measure of the angle between the sides, Y = 52°

The formula for finding the area of a parallelogram is given as follows;

Area of a parallelogram = A·B·sin(Y)

Where;

'A' and 'B' are the length of the parallel sides and 'Y' is the measure of the angle between them

Let 'A' and 'B' represent the 65 feet and the 87 feet respectively, we get;

Area of the parallelogram = 65 ft. × 87 ft. × sin(52°) ≈ 4,456.2 ft.²

According to the question a trinomial with a leading coefficient of 3 and a constant term of -5 would be 3x² + x - 5.

A trinomial is a polynomial with three terms is in the form of Ax²+Bx+C, where, A is the leading coefficient of veriable X²,  B is the middle coefficient of x and C is the constant of polynomial.

A trinomial with a leading coefficient of 3 and a constant term of -5.

Here, a=3,c=-5 and consider b=1,

Therefore, a trinomial with a leading coefficient of 3 and a constant term of -5 would be 3x² + x - 5.

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Decomposition is used to perform ANOVA and test the significance of the independent variable and its interaction effect on the dependent variable.

The expression SS stands for "sum of squares", which is a statistical concept used in analysis of variance (ANOVA) to quantify the variation in a dataset. The components of this expression, a, b, c, and d, represent different sources of variation in the dataset, and their meanings are as follows:

a. (df)(s^2): This component represents the sum of squares due to the effect of the independent variable, also known as the factor or treatment. It is calculated by multiplying the degrees of freedom (df), which is the number of levels of the factor minus one, by the variance of the data within each level (s^2). This component quantifies the amount of variation in the dependent variable that can be explained by the independent variable.

b. (df)(s): This component represents the sum of squares due to the interaction between the independent variable and other factors, also known as the interaction effect. It is calculated by multiplying the degrees of freedom (df) by the standard deviation (s) of the data. This component quantifies the amount of variation in the dependent variable that is due to the joint effect of the independent variable and other factors.

c. (n)(s^2): This component represents the sum of squares due to the variation within groups, also known as the error or residual sum of squares. It is calculated by multiplying the sample size (n) by the variance of the data within each group (s^2). This component quantifies the amount of variation in the dependent variable that is not explained by the independent variable or other factors.

d. (n)(s): This component represents the sum of squares due to the variation between the sample mean and the overall mean, also known as the total sum of squares. It is calculated by multiplying the sample size (n) by the standard deviation (s) of the data. This component quantifies the total amount of variation in the dependent variable.

In summary, the expression SS = a. (df)(s^2) + b. (df)(s) + c. (n)(s^2) + d. (n)(s) represents the decomposition of the total sum of squares into its components due to the independent variable, interaction effect, error, and total variation. This decomposition is used to perform ANOVA and test the significance of the independent variable and its interaction effect on the dependent variable.

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Max profit would be 54 type 1 and 88 type 2

A branch of mathematics known as algebra deals with symbols and the mathematical operations performed on them.

Variables are the name given to these symbols because they lack set values.

In order to determine the values, these symbols are also subjected to various addition, subtraction, multiplication, and division arithmetic operations.

given:

Let x be the amt of type 1 and y be the amt of type 2.

Then, Storage constraints

x ≤ 100

y ≤ 150

and, Mixing constraint:

62x + 44y ≤ 7220

44y = 7220-62x

y = 164 - 1.4x

and, Packaging constraint:

78x + 46y ≤ 8260

46y = 8260 - 78x

y = 180 - 1.7 x

Then, The objective functions for each corner of the region

solve:

62x + 44y = 7220

78x + 46y = 8260

So, x=54,y=88

Hence, Max profit would be 54 type 1 and 88 type 2

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Answer:

26 because 30-4=26

Step-by-step explanation:

Answer:

Plots that can detect violations in regression assumptions, while response plots help analyse the relationship between the response variable and predictors are Residual plots and scatterplot matrix.

Step-by-step explanation:

There are several graphical plots commonly used to detect violations of regression model assumptions and analyze estimated regression models. Here are a few examples:

Residual plot: A residual plot shows the difference between the observed values of the response variable and the predicted values from the regression model. Patterns in the residuals, such as nonlinearity, heteroscedasticity (unequal variances), or outliers, can indicate violations of assumptions.

Response plot: This plot examines the relationship between the response variable and one of the predictor variables while holding other predictors constant. It helps identify nonlinearity or other issues in the relationship between the response and predictors.

Scatterplot matrix: A scatterplot matrix displays scatterplots between pairs of predictor variables. It can help detect issues like perfect multicollinearity, which occurs when two or more predictors are highly correlated, leading to problems in estimating the regression coefficients.

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