Estimation (gcse maths)

Descriptive statistics is a branch of statistics that deals with the collection, analysis, interpretation, and presentation of data. It focuses on summarizing and describing the characteristics of a sample or population. The purpose of descriptive statistics is to provide a clear and concise summary of the data, including measures of central tendency, variability, and distribution.

True,This information can be used to make inferences about the population as a whole. Therefore, descriptive statistics helps statisticians to better understand and interpret the population data.

False, Descriptive statistics is a branch of statistics that focuses on summarizing and organizing data from a sample or population. It provides insights into the basic features of the data, such as the mean, median, and standard deviation, but does not make inferences about the population.

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The point that could be the location of the other end of the wall will be (0, 5).

By using one or more elements or coordinates, a reference frame can properly pinpoint location alongside other mathematical components on such space, including Euclidean space.

A point or object in a two-dimensional plane can be found by utilizing its coordinates, which appear to be sets of integers. The y and x vectors can be used to identify the position of a point on a double surface. a group of photos used to identify certain areas.

In conclusion, the point that could be the location of the other end of the wall will be (0, 5).

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A)  The demand function is [tex]y = 500 - 20x[/tex]

B) The revenue function [tex]R(x) = 500x - 20x^2[/tex]

C) The marginal revenue [tex]MR(x) = 500 - 40x[/tex]

D) This means that the store can maximize its revenue by setting the price at $25

E) The price corresponding to the value found in part d) is $25

To determine the demand function, we need to use the information given in the problem that for each $1.50 decrease in price, sales will increase by 5 travel mugs. Let x be the price in dollars and y be the number of travel mugs sold.

A) Then, we can write the demand function as:

[tex]y = 140 + 5((24-x)/1.5)[/tex]

Simplifying this expression, we get:

[tex]y = 140 + 20(16 - x)[/tex]

[tex]y = 500 - 20x[/tex]

Therefore, the demand function is[tex]y = 500 - 20x.[/tex]

B) The revenue function is given by the product of the price and the quantity sold:

[tex]R(x) = x(500 - 20x)[/tex]

[tex]R(x) = 500x - 20x^2[/tex]

C) The marginal revenue is the derivative of the revenue function with respect to x:

[tex]MR(x) = dR/dx[/tex]

[tex]= 500 - 40x[/tex]

D) To solve for R(x) = 0, we need to set the revenue function equal to zero and solve for x:

[tex]500x - 20x^2 = 0[/tex]

[tex]x(500 - 20x) = 0[/tex]

[tex]x = 0[/tex] or [tex]x = 25[/tex]

Since the price cannot be zero, the store can only set the price at $25 to achieve zero revenue. This means that the store can maximize its revenue by setting the price at $25.

E) The price corresponding to the value found in part d) is $25.

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The scatter plot shows that there is no strong correlation between average weight and life expectancy for the 12 dog breeds. The coefficient of correlation for this adult weight data to be -0.123, which is very near to 0.

The adult weight of a person can vary greatly depending on several factors, including genetics, age, gender, height, muscle mass, and overall health. However, a healthy weight range for adults is typically determined by body mass index (BMI), which is calculated by dividing weight in kilograms by height in meters squared.

We can use the average weight as the x-value and the average life expectancy as the y-value to represent the data as ordered pairs. Following are the ordered pairs for the provided data:

(125, 57.5)

(62.5, 49)

(12, 16)

(12.3, 12)

(11, 11)

We may plot these ordered pairs on a scatter plot to show the form of the data. As for the story:

We can observe from the scatter plot that there is no obvious pattern formed by the data points. There is no discernible pattern or connection between the two variables, and the spots are dispersed throughout the plot. As a result, the data's shape can be described as random or dispersed.

We can calculate the correlation coefficient to provide more evidence for this. The variables do not have a linear relationship if the correlation coefficient is close to zero. we can calculate the coefficient of correlation for this data to be -0.123, which is very near to 0.

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From the addition arithematic operation, the total number of sold computers by Mr victor is equals to ninty-three out of hundard computers .

Addition, subtraction, multiplication, and division are four basic arithmetic operations used in mathematics.

Total number of computers Mr victor has

= 100

Number of computers sold by him in morning = w

Number of computers sold by him in afternoon = 2w + 3

Number of computers left after selling = 7

We have to determine the number of computers he had to sell. We have total counts of computers so we equate all sold and unsold computers to total and will determine value of variable w. Using addition, w + 2w + 3 + 7 = 100

Simplify, 3w + 10 = 100

=> 3w = 90

Dividing by 3 both sides,

=> w = 30

So, Number of computers sold in morning = 30

Number of computers sold in afternoon = 2×30 + 3 = 63

So, total sold computers = 63 + 30 = 93.

Hence, required value is 93.

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The table showing the exponential function is completed and presented below  

x      y

0    96

1    192

2   384

3   768

The expression for the table is given as

y = a * b^x,

Point (0, 96) is on the table.

a = 96,

when b = 2, we have that

for x = 1

y = 96 x 2^x = 96 x 2^1 = 192

for x = 2

y = 96 x 2^x = 96 x 2^2 = 384

for x = 3

y = 96 x 2^x = 96 x 2^3 = 768

Therefore, The required exponential function will be  

x      y

0    96

1    192

2   384

3   768

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The number of smaller triangles used to fill the larger triangle is given as follows:

1024 triangles.

The perimeter of the larger triangle is 32 times larger than the perimeter of one of the smaller triangles, which means that the ratio of the areas is given as follows:

32² = 1024.

The ratio of the areas is obtained squared as the perimeter is measured in units, while the area is measured in units squared.

This means that 1024 smaller triangles are needed to fill the larger triangle.

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1. The quadratic regression model is [tex]Y = b0 + b1X + b2X^2[/tex] . The regression coefficient b2 represents the rate of change in muscle mass with respect to age squared. 2. The quadratic term can not be dropped from the regression model, since the calculated F-value is less than the critical value. 3. The fitted regression function in terms of the original variable X is [tex]Y = 87.017 + 0.241X - 0.002X^2[/tex].

To determine the quadratic regression model follow these steps:

1. Using R program, the quadratic regression model:

[tex]Y = b0 + b1X + b2X^2[/tex]

where Y is the muscle mass, X is the age.

The regression coefficients are:

b0 = 283.962

b1 = -14.501

b2 = 0.162

The regression coefficient b2 (quadratic term) represents the rate of change in muscle mass with respect to age squared. It measures the acceleration or deceleration of the change in muscle mass as the age increases.

2. Using the F-test.

[tex]F = [SSR(x,x^2) - SSR(x)] / [(k - 1) * MSE][/tex]

where k = number of coefficients = 3 (b0, b1, b2).

MSE = Mean Squared Error = 47.086

[tex]SSR(x,x^2), SSR(x) =[/tex] Sum of Squares due to Regression with both X and [tex]X^2[/tex]  as predictors = 230.74, due to Regression with only X as predictor = 135.03

Therefore,

[tex]F = [230.74 - 135.03] / [(3 - 1) * 47.086] = 2.214[/tex]

Using a significance level the critical value for F-test is 5.143.

Since the calculated F-value (2.214) is less than the critical value (5.143), we fail to reject the null hypothesis. Therefore, there is not enough evidence that quadratic term can be dropped from regression model.

3. The fitted regression function in terms of the original variables:

[tex]Y = 87.017 + 0.241X - 0.002X^2[/tex]

where X is the age and Y is the measure of muscle mass.

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Answer: 2/3 or 12/18

Step-by-step explanation:

From percentage formula, in a vine gunshot sound effect download unblocked restaurants, the number of expected Italian restaurants in next 24 menus slipped under Eli's door is six.

We have a Vine gunshot sound effect download unblocked Restaurants often slip takeout menus. Total collected menus by Eli = 28

In this 28 menus, 7 for Italian food. We have to determine the how many menus in next 24 menus slipped under Eli's door expected from Italian restaurants. Percentage is calculated by dividing the value by the total value, and then multiplying the resultant value by 100.

Using percentage formula, 7 are Italian food out of all 28 that is total [tex]\frac{7 {28} × 100 = 25\%[/tex].

Let the required number of menus slipped under Eli's door should you expect to be from Italian restaurants be x. So, number of menus slipped under Eli's door should you expect to be from Italian restaurants out of 24, x = 25% of 24

=> [tex]\frac{25}{100} × 24 = x[/tex]

=> x = 6

Hence, required value is 6.

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Answer:

64.141 cm ^2

Step-by-step explanation:

Formula for solving this is Pi(7^2) (170/360)

170 being the angle in degrees.

The interval that contains the median temperature is 70-79 in the frequency table showing the observed high temperatures in Buffalo.

First, we need to calculate the total number of observations, which is 5+12+9+5=31.

The median is the middle value of the data set when arranged in ascending or descending order. Since there are 31 observations, the median will be the 16th value.

To determine which interval contains the median temperature, we need to calculate the cumulative frequency of each interval. The cumulative frequency for the first interval is 5, for the second interval it is 5+12=17, for the third interval it is 17+9=26, and for the fourth interval it is 26+5=31.

Since the median is the 16th value, it lies within the third interval, which is 70-79.

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The question is -

The following frequency table shows the observed high temperatures in Buffalo, New York, in May 2007. Which interval contains the median temperature?

temperature                     frequency

50-59                                 5

60-69                                 12

70-79                                  9

80-89                                 5

The equation of the line written in general form (4,5) (1,2) is y - x = 1.

The formula to find the line equation from two points is as follows -

(y - [tex] y_{1}[/tex])/(x - [tex] x_{1}[/tex]) = ([tex] y_{2}[/tex] - [tex] y_{1}[/tex])/([tex] x_{2}[/tex] - [tex] x_{1}[/tex]). In the formula, [tex] y_{1}[/tex] and [tex] y_{2}[/tex] are initial and final y-axis values and [tex] x_{1}[/tex] and [tex] x_{2}[/tex] are initial and final x-axis values.

Keep the values in formula to find the equation -

(y - 5)/(x - 4) = (2 - 5)/(1 - 4)

Simplifying the equation

(y - 5)/(x - 4) = -3/-3

Divide the values

(y - 5)/(x - 4) = 1

Rewriting the equation

(y - 5) = (x - 4)

Rearranging the equation

y - x = 5 - 4

y - x = 1

Hence, the equation of line is y - x = 1.

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The average speed of the buses is approximately 19.08 miles per hour.

We have,

If the trip takes 3 hours and 15 minutes of driving time, that's a total of 3.25 hours.

The distance traveled is 124 miles round trip, so the distance traveled in one direction is half of that or 62 miles.

To find the average speed of the buses in miles per hour, we can use the formula:

average speed = distance/time

where distance is in miles and time is in hours.

So, the average speed of the buses in miles per hour is:

Average speed

= 62 miles / 3.25 hours

= 19.0769 miles per hour (rounded to 4 decimal places)

Therefore,

The average speed of the buses is approximately 19.08 miles per hour.

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Answer: m∠1=76.5

Step-by-step explanation:

x+y/2

71+82/2

153/2

76.5

Hope this helps! :)

Answer:

Stem | Leaf

1| 9

2| 5 9

3| 0 3 3 8

4| 0 7 9

5| 4 5

6| 1 5

7| 2 7

8| 1

Step-by-step explanation:

Minimum: 19

Maximum: 81

Range: 62

Count: 17

Sum: 808

Mean: 47.53

Median: 47

Mode: 33

Standard Deviation: 18.9

Variance: 357.3

The president of Doerman Distributors, Inc., believes that 27% of the firm's orders come from first-time cu:

sample of 100 orders will be used to estimate the proportion of first-time customers. Use z-table.

0.30. What is the sampling distribution of p for this study?

a. Assume that the president is correct and p

=

Hint(s) Che

A normal distribution because np and n(1-p) are both greater than 5 v

b. What is the probability that the sample proportion will be between 0.20 and 0.40 (to 4 decimals)?

c. What is the probability that the sample proportion will be between 0.25 and 0.35 (to 4 decimals)?

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Partially Correct

Answer:

Step-by-step explanation:

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a. Since the sample size is large enough (n=100) and the expected number of first-time customers (np=27) and the expected number of repeating customers (n(1-p)=73) are both greater than 5, we can assume that the sampling distribution of the sample proportion p is approximately normal with mean μ=p=0.27 and standard deviation σ=sqrt[p(1-p)/n]=sqrt[(0.27)(0.73)/100]=0.046.

b. To find the probability that the sample proportion will be between 0.20 and 0.40, we need to standardize the values using the formula z = (x - μ) / σ, where x is the sample proportion, μ is the population proportion, and σ is the standard deviation of the sampling distribution of p. Then we can use a standard normal distribution table (z-table) to find the corresponding probabilities.

z(0.20) = (0.20 - 0.27) / 0.046 = -1.52

z(0.40) = (0.40 - 0.27) / 0.046 = 2.83

Using the z-table, the probability of getting a z-score between -1.52 and 2.83 is approximately 0.9747. Therefore, the probability that the sample proportion will be between 0.20 and 0.40 is 0.9747 (to 4 decimals).

c. To find the probability that the sample proportion will be between 0.25 and 0.35, we can follow the same steps as in part b:

z(0.25) = (0.25 - 0.27) / 0.046 = -0.43

z(0.35) = (0.35 - 0.27) / 0.046 = 1.74

Using the z-table, the probability of getting a z-score between -0.43 and 1.74 is approximately 0.5267. Therefore, the probability that the sample proportion will be between 0.25 and 0.35 is 0.5267 (to 4 decimals).

The Intermediate Value Theorem states that for any value c between the function's values at the endpoints (f(a) and f(b)), there exists a value x in the interval [a, b] such that f(x) = c.

The assumptions (or conditions) required for the Intermediate Value Theorem are:

1. The function is continuous: The function must be continuous on the closed interval [a, b]. This means that there are no breaks, jumps, or holes in the graph of the function within the given interval.

2. The interval is closed and bounded: The interval [a, b] must be a closed interval, meaning it includes both endpoints a and b. Additionally, the interval must be bounded, meaning the function has a maximum and a minimum value within the interval.

By satisfying these two assumptions, the Intermediate Value Theorem states that for any value c between the function's values at the endpoints (f(a) and f(b)), there exists a value x in the interval [a, b] such that f(x) = c.

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The true population proportion and the sample proportion, given the confidence level and sample size.

In statistics, P-hat represents the sample proportion and E represents the margin of error.

Given a confidence interval of (0.444, 0.484), we can find P-hat and E as follows:

P-hat = (lower limit + upper limit) / 2

P-hat = (0.444 + 0.484) / 2

P-hat = 0.464

Therefore, the sample proportion (P-hat) is 0.464.

To find E (the margin of error), we need to use the formula:

E = (upper limit - lower limit) / 2

E = (0.484 - 0.444) / 2

E = 0.02

Therefore, the margin of error (E) is 0.02.

Note that the margin of error indicates the maximum likely difference between the true population proportion and the sample proportion, given the confidence level and sample size.

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The dimension available for the design is the lateral surface area of the can, which is approximately 251.33 square centimeters.

The area between the bases of the can is the lateral surface area of the can, which can be calculated using the formula:

Lateral surface area = 2 x π x r x h

where π is the mathematical constant pi (approximately 3.14159), r is the radius of the can (which is half of the diameter), and h is the height of the can.

In this case, the height of the can is given as 9.4 centimeters, and the diameter (and hence the radius) is given as 8.5/2 = 4.25 centimeters.

Plugging in these values, we get:

Lateral surface area = 2 x π x 4.25 cm x 9.4 cm

= 251.327 square centimeters

Therefore, the dimension available for the design is the lateral surface area of the can, which is approximately 251.33 square centimeters.

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i) Based on exponential growth, Xavier's salary in 2015 is £44,274.

ii) The year that Xavier's salary first became greater than £47,500 would be 2019.

Exponential functions show the relationship between two variables and a variable exponent with a periodic constant rate of growth or decay in the value of something

Annual increase in Xavier's salary = 2% or 0.02

Xavier's salary in 2010 = £40,100

The number of years between 2015 and 2010 = 5 years

i) y = £40,100(1.02)^5

= £44,273.64

= £44,274

ii) £47,500 = £40,100(1.02)^t

t = 9 years

= 2019 (2010 + 9)

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The solution of the quadratic equation, 40 = x² - 3x is x = 8 or x = -5.

Quadratic equation can be represented as follows:

ax²+ bx + c

where

Therefore, let's solve the quadratic equation as follows:

40 = x² - 3x

Hence,

x² - 3x - 40 = 0

x² + 5x - 8x - 40 = 0

x(x + 5) - 8(x + 5) = 0

(x - 8)(x + 5) = 0

x = 8 or x = -5

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An assembly time, chain saw requires 5 hours of assembly and a wood chipper 2 hours. From linear programming for maximum profit, number of chain saw assembled are 0 and number of wood chipper are 10.

This problem is related to the topic of linear programming. We use a graphical method to solve the equation. To determine the maximum profit we write the equation of profit. Let we consider x chain saw and y wood chipper. We have a chain saw requires 5 hours of assembly. But wood chipper require 2 hours of assembly. Maximum hours of assembly time available = 20 hours

So, 5x + 2y ≤ 20 --(1) and x ≥ 0, y≥ 0

Profit of chain saw = $190

Profit on wood chipper = $210

Maximize profit, Max Z = 190x + 210y

Now, using graphical method, draw a graph is present in above figure. To determine the profit at point A and B

At point A( 0, 10)

Z = 190 ×(0)+ 210× (10) = 2100 --(1)

At point B(5,0)

Z = 190×(5)+230×(0) = 950 --(2)

Clearly from equation (1), maximum profit is at point A, number of chain saw assembled are 0 and number of wood chipper arre 10.

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Of course! I'm here to help. Please provide me with the details or information you need assistance with regarding Pete, the skateboarding penguin and the right triangular prism ramp. I'll do my best to provide you with prompt and accurate help.

The postfix expression for the given infix expression is "A B C * + D +".

To convert the infix expression "A+B*C+D" to postfix expression using a stack, we can follow these steps:

Create an empty stack and an empty output queue.

Process each symbol in the infix expression from left to right.

If the symbol is an operand (e.g. A, B, C, D), add it to the output queue.

If the symbol is an operator (e.g. +, *), then do the following:

a. While the stack is not empty and the top of the stack has greater precedence than or equal precedence to the current operator, pop the top of the stack and add it to the output queue.

b. Push the current operator onto the stack.

After processing all the symbols in the infix expression, pop any remaining operators from the stack and add them to the output queue.

Using this algorithm, we can convert the infix expression "A+B*C+D" to postfix expression as follows:

Symbol: A + B * C + D

Action: Push A Push + Push B Push * Push C Pop * Pop + Push D

Output: A B C * + D +

Therefore, the postfix expression for the given infix expression is "A B C * + D +".

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At the end of three years, Daniel would have saved $6749.

When interest is calculated on a principal amount of money using the compound interest method, the interest gained is periodically added back to the principal and interest is then calculated on the new principal amount.

We know that;

A = P(1 + r/n)^nt

A =amount

r = rate

P = principal

n = Number of times compounded

t = time

Thus;

A = 6000(1 + 0.04)^3

A = $6749

Thus the compound amount saved is  $6749

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Note that the coordinates of V after it has been reflected over the x-axis will be: V' (3, -5)

The coordinates given are

V (3, 5)

W(5,8)

X (9, 6)

y (3, 3)

When point is reflected over the x- ais, it's y - coordinate takes on a polarized sign that is it goes from positive to negative of vice versa while the x-cordinte remains the same

So after the image on point v hs been reflected, the new coordinates for V = V' = (3, -5)

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The probability that the average amount of data used in this sample was greater than 632 megabytes is approximately 0.1922 or 19.22%.

a. The mean of the sample mean (my) can be calculated using the formula:

my = population mean = 606 megabytes per month

b. The standard deviation (standard error) of the sample mean can be calculated using the formula:
standard error = [tex]\frac{standard deviation}{\sqrt{sample size} }[/tex]
standard error = [tex]\frac{240}{\sqrt{64} }[/tex]
standard error = 30

Therefore, the standard error of the sample mean is 30 megabytes per month.

c. To find the probability that the average amount of data used in this sample was greater than 632 megabytes, we need to use the formula for the z-score:
z = [tex]\frac{(x - my) }{standard error}[/tex]
where x is the sample mean, my is the population mean, and standard error is the standard error of the sample mean.
z = [tex]\frac{(632 - 606) }{30}[/tex]
z = 0.87

Using a z-table or calculator, we can find that the probability of getting a z-score of 0.87 or higher is 0.1922. Therefore, the probability that the average amount of data used in this sample was greater than 632 megabytes is approximately 0.1922 or 19.22%.

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Answer: Geometry is a branch of mathematics that deals with the study of shapes, sizes, positions, and measurements of objects in two-dimensional and three-dimensional spaces. It involves analyzing and calculating angles, lengths, areas, volumes, and other properties of various figures such as triangles, circles, squares, cubes, and spheres. Geometry is used in many fields including architecture, engineering, physics, and computer graphics.