Erica found the mean of the yearly incomes of a sample of households in her hometown as shown in the chart below. In a report, she stated, she stated, "the typical income in my neighborhood is about $81,500 per year." How is this misleading?
A) The mean of the data is not about $81,500.
B) Erica's statement is not misleading.
C) The mean is not good measure of the incomes because a few higher incomes pull the mean higher moat if the household incomes.
D) The mean is not good measure of the incomes because the lower incomes pull the mean lower than most household incomes.
A?
the answer is a
sorry - can't see files on your computer.
so what's the answer
because she didn't reveal her data!
Yes, the answer is A. It is misleading because the mean of the data is not about $81,500. The mean is influenced by extreme values and may not provide an accurate reflection of the typical income in the neighborhood.
im stuck on same thing
What's the answer??
a?
Display the data in a histogram.
Retirement Ages of Police Detectives
Age
Tally
Frequency
50–52
||
2
53–55
||||
5
56–58
||||
5
59–61
||||
5
62–64
|||| |||
8
65–67
||||
5
A. frequency histogram A bar diagram has a horizontal axis labeled Retirement Age. It is divided into the following groups: 50 to 52, 53 to 55, 56 to 58, 59 to 61, 62 to 64, and 65-67. The vertical axis is labeled Frequency and shows numbers from 0 to 14. The 50 to 52 bar has a frequency of 2. The 53 to 55 bar has as frequency of 4. The 56 to 58 bar has as frequency of 4. The 59 to 61 bar has as frequency of 4. The 62 to 64 bar has as frequency of 8. The 65 to 67 bar has as frequency of 6.
B. frequency histogram A bar diagram has a horizontal axis labeled Retirement Age. It is divided into the following groups: 50 to 52, 53 to 55, 56 to 58, 59 to 61, 62 to 64, and 65-67. The vertical axis is labeled Frequency and shows numbers from 0 to 14. The 50 to 52 bar has a frequency of 4. The 53 to 55 bar has as frequency of 6. The 56 to 58 bar has as frequency of 6. The 59 to 61 bar has as frequency of 6. The 62 to 64 bar has as frequency of 8. The 65 to 67 bar has as frequency of 6.
C. frequency histogram A bar diagram has a horizontal axis labeled Retirement Age. It is divided into the following groups: 50 to 52, 53 to 55, 56 to 58, 59 to 61, 62 to 64, and 65-67. The vertical axis is labeled Frequency and shows numbers from 0 to 14. The 50 to 52 bar has a frequency of 6. The 53 to 55 bar has as frequency of 8. The 56 to 58 bar has as frequency of 8. The 59 to 61 bar has as frequency of 8. The 62 to 64 bar has as frequency of 12. The 65 to 67 bar has as frequency of 6.
D. frequency histogram A bar diagram has a horizontal axis labeled Retirement Age. It is divided into the following groups: 50 to 52, 53 to 55, 56 to 58, 59 to 61, 62 to 64, and 65-67. The vertical axis is labeled Frequency and shows numbers from 0 to 14. The 50 to 52 bar has a frequency of 2. The 53 to 55 bar has as frequency of 5. The 56 to 58 bar has as frequency of 5. The 59 to 61 bar has as frequency of 5. The 62 to 64 bar has as frequency of 8. The 65 to 67 bar has as frequency of 5.
B. frequency histogram A bar diagram has a horizontal axis labeled Retirement Age. It is divided into the following groups: 50 to 52, 53 to 55, 56 to 58, 59 to 61, 62 to 64, and 65-67. The vertical axis is labeled Frequency and shows numbers from 0 to 14. The 50 to 52 bar has a frequency of 2. The 53 to 55 bar has a frequency of 5. The 56 to 58 bar has a frequency of 5. The 59 to 61 bar has a frequency of 5. The 62 to 64 bar has a frequency of 8. The 65 to 67 bar has a frequency of 5.
Which display is best to determine the relationship between the number of hours worked and the amount of money paid?
A. histogram with intervals of 5
B. histogram with intervals of 3
C. line plot
D. line graph
D. Line graph is the best display to determine the relationship between the number of hours worked and the amount of money paid. A line graph shows the relationship between two variables, with one variable represented on the x-axis and the other variable represented on the y-axis. This allows us to plot the data points and connect them with a line, which helps us to see any patterns or trends in the data. This would be ideal for showing the relationship between hours worked and money paid, as it allows us to see how the amount of money paid changes with the number of hours worked.
Carrie asked 50 randomly selected middle school students at King’s High School about their favorite fast food item. Twenty-one selected french fries. If there are 350 middle school students at King’s High School, estimate how many will select french fries as their favorite fast food.
A. 141
B. 147
C. 153
D. 159
B. 147 is the estimated number of students who will select french fries as their favorite fast food.
To estimate, we can set up a proportion:
21/50 = x/350
where x is the unknown number of students who will select french fries in the entire school. Cross-multiplying, we get:
50x = 21 * 350
Simplifying, we get:
x = (21 * 350) / 50 = 147
Therefore, we estimate that 147 middle school students at King's High School will select french fries as their favorite fast food.
The table below shows data Jessie collected on the fat and calorie content of different foods. Which scatter plot represents the given data?
Fat Grams 3 7 9 10 14 22 23 26
Calories 100 180 300 450 575 620 580 600
A. A scatter plot is shown.The x-axis is labeled Fat Grams and has numbers from 0 to 30 with a step size of 10. The y-axis is labeled Calories and has numbers from 0 to 800 with a step size of 200. The scatter plots shows these approximate points: left-parenthesis 5 comma 700 right-parenthesis, left-parenthesis 8 comma 650 right-parenthesis, left-parenthesis 10 comma 600 right-parenthesis, left-parenthesis 15 comma 400 right-parenthesis, left-parenthesis 18 comma 300 right-parenthesis, left-parenthesis 25 comma 200 right-parenthesis, and left-parenthesis 28 comma 100 right-parenthesis.
B. A scatter plot is shown.The x-axis is labeled Fat Grams and has numbers from 0 to 30 with a step size of 10. The y-axis is labeled Calories and has numbers from 0 to 400 with a step size of 100. The scatter plots shows these approximate points: left-parenthesis 3 comma 50 right-parenthesis, left-parenthesis 8 comma 100 right-parenthesis, left-parenthesis 9 comma 150 right-parenthesis, left-parenthesis 10 comma 200 right-parenthesis, left-parenthesis 15 comma 290 right-parenthesis, left-parenthesis 22 comma 300 right-parenthesis, left-parenthesis 25 comma 300 right-parenthesis, and left-parenthesis 29 comma 350 right-parenthesis.
C. A scatter plot is shown.The x-axis is labeled Calories and has numbers from 0 to 800 with a step size of 200. The y-axis is labeled Fat Grams and has numbers from 0 to 30 with a step size of 5. The scatter plots shows these approximate points: left-parenthesis 100 comma 3 right-parenthesis, left-parenthesis 200 comma 7 right-parenthesis, left-parenthesis 300 comma 9 right-parenthesis, left-parenthesis 450 comma 10 right-parenthesis, left-parenthesis 600 comma 13 right-parenthesis, left-parenthesis 600 comma 23 right-parenthesis, left-parenthesis 600 comma 26 right-parenthesis, and left-parenthesis 650 comma 22 right-parenthesis.
D. A scatter plot is shown.The x-axis is labeled Fat Grams and has numbers from 0 to 30 with a step size of 10. The y-axis is labeled Calories and has numbers from 0 to 800 with a step size of 200. The scatter plots shows these approximate points: left-parenthesis 3 comma 100 right-parenthesis, left-parenthesis 8 comma 200 right-parenthesis, left-parenthesis 10 comma 300 right-parenthesis, left-parenthesis 10 comma 400 right-parenthesis, left-parenthesis 15 comma 600 right-parenthesis, left-parenthesis 20 comma 600 right-parenthesis, left-parenthesis 23 comma 650 right-parenthesis, and left-parenthesis 28 comma 700 right-parenthesis.
D. A scatter plot is shown. The x-axis is labeled Fat Grams and has numbers from 0 to 30 with a step size of 10. The y-axis is labeled Calories and has numbers from 0 to 800 with a step size of 200. The scatter plot shows these approximate points: (3, 100), (8, 200), (10, 300), (10, 400), (15, 600), (20, 600), (23, 650), and (28, 700).
This scatter plot represents the given data because it shows the relationship between fat grams and calorie content. The points on the scatter plot show that as the fat grams increase, the calorie content also tends to increase. The points are relatively close to a straight line, which indicates that there is a strong positive correlation between the variables.
You are surveying students to find out their opinion of the quality of food served in the school cafeteria. You decide to poll only those students who buy hot lunch at the school cafeteria on a particular day. Is your sample random? Explain, but in a short answer.
No, the sample is not random because it only includes students who buy hot lunch at the school cafeteria on a particular day. This type of sample is called a convenience sample, where the sample is selected based on its availability and accessibility. It may not be representative of the entire student population who eat at the cafeteria, as those who bring their lunch from home or go out to eat are not included in the sample. Therefore, the results of the survey may not be generalized to the entire student population and may be biased towards the opinions of hot lunch buyers.
The table shows the rainfall, in inches, in the month of July for the years 2006 through 2011.
Year
2006
2007
2008
2009
2010
2011
Rainfall
4.5
4.4
4.1
4.2
3.9
4.0
Alex used the data to make the graph below.
A line graph representing the data in the table is shown.A line graph is titled July Rainfall.
The horizontal axis is labeled Year and is equally spaced. The axis scale starts at 2006 increases by 1 until ending at 2011.
The vertical axis is labeled Rainfall in inches and is equally spaced. The axis scale starts at 3.6 and increases by 0.1 until ending at 4.6.
The data points represented in the tabled are connected by line segments from left to right.
a) In what way could the graph be misleading?
b) How could you redraw the graph so that it is less misleading?
a) The graph could be misleading because the difference between the minimum and maximum values on the vertical axis is relatively small (only 1 inch), while the distance between the tick marks on the axis is also small (only 0.1 inch). This makes the differences in rainfall appear much larger than they actually are. The differences between the years are exaggerated, making it seem like there is more variation between the years than there actually is.
b) To make the graph less misleading, we could redraw it with a larger vertical axis scale. For example, instead of ranging from 3.6 to 4.6 with tick marks every 0.1 inches, we could use a scale that ranges from, say, 3 to 5 with tick marks every 0.5 inches. This would help to better show the relatively small changes in rainfall over the years while still allowing us to see any patterns or trends in the data. Alternatively, we could use a bar chart or a dot plot to display the data, rather than a line graph, which may be more appropriate for this type of data.