Use the given data to complete parts (a) and (b) below. x | y
---|---
2.3 | 4
3.9 | 1.5
2.8 | 3.6
4.7 | 4.9 Compute the linear correlation coefficient with the additional data point. The linear correlation coefficient for the five pieces of data is .
(Round to three decimal places as needed.) Comment on the effect the additional data point has on the linear correlation coefficient. A. The additional data point does not affect the linear correlation coefficient.
B. The additional data point strengthens the appearance of a linear association between the data points.
C. The additional data point weakens the appearance of a linear association between the data points. Explain why correlations should always be reported with scatter diagrams. A. The scatter diagram can be used to distinguish between association and causation.
B. The scatter diagram is needed to see if the correlation coefficient is being affected by the presence of outliers.
n=2317x=411
A survey of 2317 adults in a certain large country aged 18 and older conducted by a reputable polling organization found that 411 have donated blood in the past two years. Complete parts (a) through (c) below. (a) Obtain a point estimate for the population proportion of adults in the country aged 18 and older who have donated blood in the past two years.
p^=
(Round to three decimal places as needed.) (b) Verify that the requirements for constructing a confidence interval about p are satisfied.
The sample a simple random sample, the value of is , which is 10, and the less than or equal to 5% of the .
(Round to three decimal places as needed.) (c) Construct and interpret a 90% confidence interval for the population proportion of adults in the country who have donated blood in the past two years. Select the correct choice below and fill in any answer boxes within your choice.
(Type integers or decimals rounded to three decimal places as needed. Use ascending order.)
A. We are % confident the proportion of adults in the country aged 18 and older who have donated blood in the past two years is between and .
B. There is a % chance the proportion of adults in the country aged 18 and older who have donated blood in the past two years is between and .
xh(x)
0 1.50
2 2.50
4 4.15 The table shows the exponential relationship between the number of years, x, since Isela started training in pole vault, and the estimated height h(x), in meters, of her best pole vault for that year. Which of the following functions best represents this relationship, where x≤4? A. h(x)=1.29(0.50)x
B. h(x)=1.29(1.50)x
C. h(x)=1.50(0.29)x
D. h(x)=1.50(1.29)x
A sample of size n=66 is drawn from a normal population whose standard deviation is σ=6.2. The sample mean is x=37.77. Part: 0 / 2 Part 1 of 2 (a) Construct a 99% confidence interval for μ. Round the answer to at least two decimal places. A 99% confidence interval for the mean is 00<μ<00.
Sleeping outlier: A simple random sample of eight college freshmen were asked how many hours of sleep they typically got per night. The results were
8.5 24 8.5 8 7.5 9 6.5 6
Send data to Excel
Notice that one joker said that he sleeps 24 a day.
Part: 0 / 3
Part 1 of 3
(a) The data contain an outlier that is clearly a mistake. Eliminate the outlier, then construct a 99% confidence interval for the mean amount of sleep from the remaining values. Round the answers to at least two decimal places.
A 99% confidence interval for the mean amount of sleep from the remaining values is < μ < .
السؤال الرابع:
الجدول التكراري التالي يمثل الأجور بمئات الدولارات لموظفي شركة بيونير للصناعات الغذائية
(أ) المطلوب: مع التوضيح تمثل البيانات باستخدام (المدرج التكراري، المنحني التكراري).
فئة الأجر التكرار x25−2015−3020−4015−50570-6080 المجموع
المدرج التكراري (0,0)
المنحني التكراري (0,0)
Classify each item as I (income statement), B (balance sheet), or CF (cash flows): Assets, Cash from operations, Equipment, Expenses, Liabilities, Net cash change, Revenues, Total liabilities & equity.
What is the total amount of money
being added to the account in the
table of deposits shown below? Deposits Amount
Incoming ACH \$2174.90
Incoming Phone Transfer \$21.78
Incoming App Transfer \$44.83
Check Mobile Deposit \$23.94 Round to the nearest cent.
\$[?]
Find a possible formula for the trigonometric function whose values are in the following table. | x | 0 | 2 | 4 | 6 | 8 | 10 | 12 |
|---|---|---|---|---|---|---|---|
| y | 2 | -2 | 2 | 6 | 2 | -2 | 2 | y=
x | 1 | 2 | 3 | 4 | 5 | 6
---|---|---|---|---|---|---|
y | 849 | 1351 | 2108 | 3224 | 4731 | 8157 Use exponential regression to find an exponential function that best fits this data. f(x)= Use linear regression to find a linear function that best fits this data. g(x)= Of these two, which equation best fits the data? Linear Exponential
Complete the table below, using the Bronsted-Lowry definition, by
entering the missing chemical formulas:
(Do not use subscripts and superscripts in your answer. Example,
H2CO4− would be written as H2CO4-) Acid | Base | Conjugate Acid | Conjugate Base
---|---|---|---
HCO3− | | NH4+ |
| OH− | | H2I
Refer to the accompanying data display that results from a sample of airport data
TInterval speeds in Mbps. Complete parts (a) through (c) below. Click the icon to view a t distribution table.
(13.046,22.15)x=17.598Sx=16.01712719n=50
a. What is the number of degrees of freedom that should be used for finding the critical value tα/2 ?
df=
(Type a whole number.)
G. Calculate the denominator of the fraction that is equal to the stated fraction with the numerator shown.
\begin{tabular}{cll}
\hline Fraction & Numerator & Denominator \\
\hline 1. 12/36 & 144 & \\
\hline 2. 84/6 & 42 & \\
\hline 3. 1/16 & 8 & \\
\hline
\end{tabular}
A pizza shop sells three sizes of pizza, and they track how
often each size gets ordered along with how much they
profit from each size. Let X represent the shop's profit on
a randomly selected pizza. Here's the probability
distribution of X along with summary statistics: | | Small | Medium | Large |
| :-------- | :---- | :----- | :---- |
| X = profit (\$) | 4 | 8 | 12 |
| \(P(X)\) | 0.18 | 0.50 | 0.32 | Mean: μX=$8.56
Standard deviation: σX=$2.77 The company is going to run a promotion where
customers get $2 off any size pizza. Assume that the
promotion will not change the probability that
corresponds to each size. Let Y represent their profit on a
randomly selected pizza with this promotion. What are the mean and standard deviation of Y? μY= ______ dollars
σY= ______ dollars
12 multiplied by 12
12 multiplied by 13
12 multiplied by 14
12 multiplied by 15
12 multiplied by 16
12 multiplied by 17
12 multiplied by 18
12 multiplied by 19
12 multiplied by 20
12 multiplied by 21
12 multiplied by 22
12 multiplied by 23
12 multiplied by 24
12 multiplied by 25
Concentration of CO2 in the Atmosphere Levels of carbon dioxide (CO2) in the atmosphere are rising rapidly, far above any levels ever before recorded. Levels were around 280 parts per million in 1800, before the Industrial Age, and had never, in the hundreds of thousands of years before that, gone above 300 ppm. Levels are now over 400 ppm. The table below shows the rapid rise of CO2 concentrations over the 55 years from 1960-2015 (data also available in Carbon Dioxide). We can use this information to predict CO2 levels in different years. | Year | CO2 |
|---|---|
| 1960 | 316.91 |
| 1965 | 320.04 |
| 1970 | 325.48 |
| 1975 | 331.11 |
| 1980 | 338.75 |
| 1985 | 346.12 |
| 1990 | 354.39 |
| 1995 | 360.82 |
| 2000 | 369.55 |
| 2005 | 379.80 |
| 2010 | 389.90 |
| 2015 | 400.81 | Concentration of carbon dioxide in the atmosphere Click here to the dataset associated with this question.
Use the 3 e version of the dataset. If using StatKey, the data needed is preloaded in the drop-down menu in the upper left corner.
Click here to access StatKey. Dr. Pieter Tans, NOAA/ESRL, http://www.esrl.noaa.gov/gmd/ccgg/trends/. Values recorded at the Mauna Loa Observatory in Hawaii. (a) What is the explanatory variable? What is the response variable?
* Year is the explanatory variable and CO2 concentration is the response variable.
CO2 concentration is the explanatory variable and Year is the response variable. (b) Use technology to find the correlation between year and CO2 levels.
Round your answer to three decimal places. (c) Use technology to calculate the regression line to predict CO2 from year.
Round your answer for the intercept to one decimal place and your answer for the slope to three decimal places.
CO2= ____ + ____ (Year) (d) Interpret the slope of the regression line, in terms of carbon dioxide concentrations.
The slope tells the predicted number of years for the CO2 level to go up by that amount.
The slope tells the predicted number of years for the CO2 level to go up by one.
The slope tells the predicted CO2 level one year later.
The slope tells the predicted change in CO2 level one year later. (e) What is the intercept of the line?
Round your answer to one decimal place.
The intercept is ____
(Does it make sense in context?) (f) Use the regression line to predict the CO2 level in 2003.
Use rounded slope and the intercept from part (c). Then round your answer to one decimal place.
CO2 level in 2003: ____ Use the regression line to predict the CO2 level in 2005.
Use rounded slope and the intercept from part (c). Then round your answer to one decimal place.
CO2 level in 2005: ____ (g) Find the residual for 2010.
Use rounded slope and the intercept from part (c). Then round your answer to two decimal places.
Residual for 2010: ____
A table of values of a linear function is shown below. x|-2|0|2|4
---|---:|---:|---:|---:
y|10|4|-2|-8 Find the y-intercept and slope of the function's graph. y-intercept: 4
slope:
John collects the running times of some athletes and records the data in the table below.
\begin{tabular}{|c|c|}
\hline Time (z seconds) & Frequency \\
\hline 50<z≤60 & 7 \\
\hline 60<z≤70 & 4 \\
\hline 70<z≤80 & 3 \\
\hline 80<z≤90 & 7 \\
\hline
\end{tabular} Find the mean of the data in the table.
Give your answer correct to 1 decimal place where appropriate.
Role model vs. Ievel of education
\begin{tabular}{lccc}
& Family member & Friend or acquaintance & Stranger \\
\hline Less than high school & 0.09 & 0.12 & 0.19 \\
High school & 0.25 & 0.32 & 0.40 \\
Some college & 0.29 & 0.25 & 0.23 \\
Bachelor's degree & 0.23 & 0.19 & 0.14 \\
Advanced degree & 0.14 & 0.12 & 0.04 \\
Column total & 1.00 & 1.00 & 1.00
\end{tabular} Based on the data, which of the following statements must be true of the people surveyed? Choose 1 answer:
(A) A person whose role model is a family member is less likely to have an advanced deffree than a person whose role model is a friend or acquaintance.
(B) A person whose role model is a stranger is more likely to have high school than some college as their highest level of education.
(C) A person whose highest level of education is a bachelor's degree is more likely to have a family member than a stranger as a role model.
(D) A person whose highest level of education is less than high school is more likely to have a stranger than a friend or acquaintance as a role model.
6. The table below give the number of homes (in thousands) build each year in a developing suburb. Find the rate of
change between 2004 and 2007 using the table. Year | Homes (thousands)
---|---
2004 | 7.1
2005 | 8.4
2006 | 9.2
2007 | 10.3
2008 | 11
A report asked people who got their news from television which television sector they relied on primarily for their news: local TV, network TV, or cable TV. The results were used to generate the data in the table below. Determine whether being female is independent of choice of local TV. Explain your answer in the context of this problem.
\begin{tabular}{|c|c|c|c|c|}
\hline & Local TV & Network TV & Cable TV & Total \\
\hline Men & 67 & 49 & 55 & \\
\hline Women & 85 & 55 & 56 & \\
\hline Total & & & & \\
\hline
\end{tabular} Since □=□ \% and □=□%, the events □ independent.
(Type integers or decimals rounded to one decimal place as needed.)
4. Caleb is comparing the growth of
plants using two different fertilizers. Group A
Group B 1 2 3 4 5
Growth (inches) Part A
Use the measures of center from the
box plots to make an inference about
the data.
A recent poll asked respondents to fill in the blank to this question: "The country when it comes to giving equal rights to women" with one of three choices. The results are shown in the accompanying table using a sample size of 80 men and 80 women. Complete parts a and b below.
\begin{tabular}{|l|c|c|c|c|}
\hline & \begin{tabular}{c}
Hasn't Gone \\
Far Enough
\end{tabular} & \begin{tabular}{c}
Has Been \\
About Right
\end{tabular} & \begin{tabular}{c}
Has Gone \\
Too Far
\end{tabular} & Total \\
\hline Men & 33 & 35 & 12 & 80 \\
\hline Women & 43 & 29 & 8 & 80 \\
\hline Total & 76 & 64 & 20 & 160 \\
\hline
\end{tabular}
A. P(male and responded "hasn't gone far enough")
B. P(hasn't gone far enough | male)
C. P (male I hasn't gone far enough)
b. Find the probability that a person randomly selected from only the men in this group responded "hasn't gone far enough." The probability is □ (Simplify your answer.)
Compare production alternatives B and D. Which statements are true: 1. More current consumption, 2. Less future consumption, 3. More future growth, 4. Less future growth?
Lottery machine outputs digits 0-9 in 200 trials. Find: (a) experimental probability of even numbers, (b) theoretical probability, (c) true statement about trials and probabilities. Round answers to nearest thousandths.
A spinner has 3 yellow, 1 red, and 1 blue slice. After 1000 spins, Jane got 606 yellow, 181 red, 213 blue. (a) Find the experimental probability of yellow or red.
(b) Find the theoretical probability of yellow or red.
(c) True statement about experimental vs theoretical probability with more spins?
Find which measures of central tendency (mean, median, mode) do not exist for the waiting times: 1, 3, 3, 5, 5, 5, 6, 12, 12, 12, 12, 13, 15, 19, 23, 27, 31, 37.
Given a survey, if the price of Apple computers is \$1,200, calculate total consumer surplus for four consumers. Choices: \$345, \$415, \$380, \$5,145.
Pour chacun des nombres, indique l'ensemble qui lui convient le mieux ( N,Z,D,Q,Q′ ).
a) 4,698
b) 3−343□
C) −48□
b) 3−343□□ d) −3,4□
e) 2065 □ f) 25π□
g) 3,1245□ h) 3,14159 □
Comparing Speeds Arnie's Airplane Distance (mi)
10
8
6
4
2 Time (min)
2 4 6 8 10 Find each slope from the graph and table to compare the constant speeds of the two airplanes. What is the constant speed (slope) of Arnie's airplane? What is the constant speed (slope) of Bernie's biplane? Who flew faster? Bernie's Biplane
Time (min) (x) | Distance (mi) (y)
------- | --------
3 | 21
5 | 35
8 | 56 Intro
Done
A manufacturer of auto windows employs a constant quality control technique where the thickness of glass is checked every hour. A perfect piece of glass will have a
thickness of 4 mm. From past experience, it is known that the standard deviation of thickness is 0.4 mm. The result of one shift's production is given in the following table.
You were asked to find the centerline for the xˉ chart. Glass Thickness (mm) | Sample | Observations | Sample | Observations |
|---|---|---|---|
| 1 | 3 6 2 4 6 | 9 | 3 6 6 3 4 |
| 2 | 4 2 2 6 5 | 10 | 4 5 2 6 5 |
| 3 | 6 3 5 5 2 | 11 | 3 5 2 3 6 |
| 4 | 2 5 3 3 6 | 12 | 5 2 4 5 3 |
| 5 | 6 4 5 3 3 | 13 | 5 5 3 4 2 |
| 6 | 5 5 5 2 4 | 14 | 5 3 4 4 5 |
| 7 | 3 6 3 4 6 | 15 | 5 6 2 2 6 |
| 8 | 5 4 3 2 5 | 16 | 4 5 3 3 6 | Recall that when the process mean is known, the xˉ chart is centered around it.
Do men score higher on average compared to women on their statistics finals? Final exam scores of thirteen randomly selected male statistics students and twelve randomly selected female statistics students are shown below. Male: 93776471726284708973638894 Female: 834658814974627069665868
Assume both follow a Normal distribution. What can be concluded at the the α=0.01 level of significance level of significance? For this study, we should use
Select an answer
a. The null and alternative hypotheses would be:
H0 :
Select an answer
Select an answer
Select an answer
(6) (please enter a decimal)
H1 :
Select an answer
Select an answer
Select an answer
(Please enter a decimal)
b. The test statistic ? 0=□ (please show your answer to 3 decimal places.)
c. The p-value =□ (Please show your answer to 4 decimal places.)
d. The p-value is
?
α
e. Based on this, we should
Select an answer
the null hypothesis.
f. Thus, the final conclusion is that ...
The results are statistically insignificant at α=0.01, so there is statistically significant evidence to conclude that the population mean statistics final exam score for men is equal to the population mean statistics final exam score for women.
The results are statistically significant at α=0.01, so there is sufficient evidence to conclude that the population mean statistics final exam score for men is more than the population mean statistics final exam score for women.
The results are statistically significant at α=0.01, so there is sufficient evidence to conclude that the mean final exam score for the thirteen men that were observed is more than the mean final exam score for the twelve women that were observed.
The results are statistically insignificant at α=0.01, so there is insufficient evidence to conclude that the population mean statistics final exam score for men is more than the population mean statistics final exam score for women.
Let y denote the number of broken eggs in a randomly selected carton of one dozen eggs.
\begin{tabular}{|c|c|c|c|c|c|}
\hliney & 0 & 1 & 2 & 3 & 4 \\
\hlinep(y) & 0.60 & 0.25 & 0.10 & 0.03 & 0.02 \\
\hline
\end{tabular}
(a) Calculate and interpret μy.
μy=□
(b) Consider the following questions.
(i) In the long run, for what percentage of cartons is the number of broken eggs less than μy ?
\%
(ii) Does this surprise you?
Yes
No
(c) Explain why μy is not equal to 50+1+2+3+4=2.0.
This computation of the mean is incorrect because it does not take into account that the number of broken eggs are all equally likely.
This computation of the mean is incorrect because the value in the denominator should equal the maximum y value.
This computation of the mean is incorrect because it does not take into account the number of partially broken eggs.
This computation of the mean is incorrect because it includes zero in the numerator which should not be taken into account when calculating the mean.
This computation of the mean is incorrect because it does not take into account the probabilities with which the number of broken eggs need to be weighted.
5. Given the following information from 1 member of a
family with a husband, a wife and 1 child. Husband's Income \$40,000 Wife's
Income \$60,000
Mortgage \$95,000 Car Loan
\$25,000
Childs Future Education Expense \$50,000
Funeral Expenses \$10,000 a. Calculate the Life Insurance needs for the Wife. b. What is your reasoning behind that dollar amount of
Life Insurance for the Wife?
A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below.
\begin{tabular}{|c|r|r|r|r|r|l|l|l|}
\hline Seeds Produced & 48 & 57 & 65 & 63 & 61 & 60 & 56 & 52 \\
\hline Sprout Percent & 57 & 54.5 & 50.5 & 50.5 & 53.5 & 51 & 61 & 66 \\
\hline
\end{tabular}
a. Find the correlation coefficient: r=□ Round to 2 decimal places.
b. The null and alternative hypotheses for correlation are:
H0:? ? =0H1:? ? =0 The p-value is: □ (Round to four decimal places)
c. Use a level of significance of α=0.05 to state the conclusion of the hypothesis test in the context of the study.
There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate.
There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful.
There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
d. r2=□ (Round to two decimal places)
e. Interpret r2 :
54% of all plants produce seeds whose chance of sprouting is the average chance of sprouting.
Given any group of plants that all produce the same number of seeds, 54% of all of these plants will produce seeds with the same chance of sprouting.
There is a 54% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced.
There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 54%.
A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below.
\begin{tabular}{|c|l|r|r|r|r|l|l|l|}
\hline Seeds Produced & 48 & 57 & 65 & 63 & 61 & 60 & 56 & 52 \\
\hline Sprout Percent & 57 & 54.5 & 50.5 & 50.5 & 53.5 & 51 & 61 & 66 \\
\hline
\end{tabular}
a. Find the correlation coefficient: r=□−0.73 Round to 2 decimal places.
b. The null and alternative hypotheses for correlation are:
H0:ρΔ2=0H1:ρ∇2=0 The p-value is: □ (Round to four decimal places)
c. Use a level of significance of α=0.05 to state the conclusion of the hypothesis test in the context of the study.
There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate.
There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful.
There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
d. r2=□ 0.54
(Round to two decimal places)
Complete the following truth table. Use T for true and F for false.
You may add more colymon put those added columns will not be graded.
\begin{tabular}{|c|c|c|c|}
\hlinep & q & ∼q→∼p & ∼p→∼q \\
\hline T & T & □ & □ \\
\hline T & F & □ & □ \\
\hline F & T & □ & □ \\
\hline F & F & □ & □ \\
\hline
\end{tabular}
⎩⎨⎧p∼□□→□xq□∧□□↦□5□∨□
302119353634282915202722253233363824
Send data to calculator (a) Complete the grouped frequency distribution for
the data. (Note that the class width is 6.)
Shopping times (in minutes) Frequency
14.5 to 20.520.5 to 26.526.5 to 32.532.5 to 38.5
Giving a test to a group of students, the grades and gender are summarized below
Grades and Gender
\begin{tabular}{|c|r|r|r|r|}
\hline & \multicolumn{1}{|c|}{ A } & B & C & Total \\
\hline Male & 19 & 10 & 18 & 47 \\
\hline Female & 2 & 3 & 9 & 14 \\
\hline Total & 21 & 13 & 27 & 61 \\
\hline
\end{tabular} If one student is chosen at random, find the probability that the student was female AND got a "C". Round your answer to 4 decimal places.
□
myopenmath.com The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995.
\begin{tabular}{|c|c|}
\hline Year & Retail Sales \\
\hline 0 & 85.851 \\
\hline 3 & 108.426 \\
\hline 6 & 141.781 \\
\hline 9 & 169.256 \\
\hline 12 & 202.297 \\
\hline 15 & 222.266 \\
\hline
\end{tabular} Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t)=9.44t+84.182. Use the above scatter plot to decide whether the linear model fits the data well.
The function is a good model for the data.
The function is not a good model for the data
Estimate the retails sales in the U. S. in 2013. □ billions of dollars.
Use the model to predict the year that corresponds to retails sales of $237 billion. □
```latex
\textbf{Problem:} Given the following data on the average number of weekly hours worked by U.S. production workers from 1967 to 1996: \begin{center}
\begin{tabular}{|c|c|}
\hline
Year & Hours Worked \\
\hline
1967 & 38.0 \\
1968 & 37.8 \\
1969 & 37.7 \\
1970 & 37.1 \\
1971 & 36.9 \\
1972 & 37.0 \\
1973 & 36.9 \\
1974 & 36.5 \\
1975 & 36.1 \\
1976 & 36.1 \\
1977 & 36.0 \\
1978 & 35.8 \\
1979 & 35.7 \\
1980 & 35.3 \\
1981 & 35.2 \\
1982 & 34.8 \\
1983 & 35.0 \\
1984 & 35.2 \\
1985 & 34.9 \\
1986 & 34.8 \\
1987 & 34.8 \\
1988 & 34.7 \\
1989 & 34.6 \\
1990 & 34.5 \\
1991 & 34.3 \\
1992 & 34.4 \\
1993 & 34.5 \\
1994 & 34.7 \\
1995 & 34.5 \\
1996 & 34.4 \\
\hline
\end{tabular}
\end{center} 1. Construct a scatter diagram and comment on the relationship, if any, between the variable Year and Hours Worked. 2. Determine and interpret the correlation for the year and hours worked. Based upon the value of the correlation, is your answer to the previous question reasonable? 3. Based upon the data given, estimate the average weekly hours worked this year. How confident are you in your estimate? You should use a linear regression model to make your prediction. 4. Assuming a linear correlation between these two variables, what will happen to the average weekly hours worked in the future? Is it possible for this pattern to continue indefinitely? Explain.
\begin{tabular}{cccc}
& Bachelor's & Master's & Doctorate \\
Men & 653,037 & 313,838 & 25,771 \\
Women & 687,564 & 315,906 & 25,253
\end{tabular} Send data to Excel Choose a degree at random. Find the probabilities of the following. Express your answer as a fraction or a decimal rounded to three decimal places. Part 1 of 4
(a) What is the probability that the degree is a bachelor's degree?
P( bachelor’s degree )=0.663 Part 2 of 4
(b) What is the probability that the degree was a master's degree or a degree awarded to a women?
P( master’s degree or awarded to woman )=0.664 Part: 2 / 4 Part 3 of 4
(c) What is the probability that the degree was a bachelor's degree awarded to a men.
P( bachelor’s degree awarded to men )=□
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A sample of blood pressure measurements is taken for a group of adults, and those values ( mm Hg ) are listed below. The values are matched so that 10 subjects each have a systolic and diastolic measurement. Find the coefficient of variation for each of the two samples; then compare the variation.
\begin{tabular}{rrrrrrrrrrr}
Systolic & 120 & 128 & 159 & 95 & 155 & 121 & 115 & 137 & 126 & 119 \\
Dᄆ 5 \\
Diastolic & 82 & 78 & 76 & 52 & 91 & 87 & 57 & 65 & 70 & 80
\end{tabular} Question 19 Question 20
The coefficient of variation for the systolic measurements is □ \%.
(Type an integer or decimal rounded to one decimal place as needed.)
Question 21 Question 22 Question 23 Question 24
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Dec 8
10:43 US
Question 14 of 25 (1 point) | Question Attempt: 1 or I College Degrees Awarded The table below represents the college degrees awarded in a recent academic year by
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gender.
\begin{tabular}{cccc}
& Bachelor's & Master's & Doctorate \\
\hline Men & 548,254 & 251,468 & 23,728 \\
Women & 609,872 & 270,538 & 23,320
\end{tabular}
Send data to Excel Choose a degree at random. Find the probabilities of the following. Express your answer as a fraction or a decimal rounded to three decimal places. Part: 0/4□ Part 1 of 4
(a) What is the probability that the degree is a doctorate?
P( doctorate )=0.027□ Part: 1/4□ Part 2 of 4
(b) What is the probability that the degree was a bachelor's degree or a degree awarded to a men?
P( bachelor’s degree or awarded to men )=□
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Copilot wig
\begin{tabular}{|c|c|c|c|c|c|c|}
\hline \multirow[b]{2}{*}{Educational Level} & \multicolumn{6}{|c|}{Houschold Income (\10UOS)} \\
\hline & Under 25 & 25.0−49.9 & 50.0−74.9 & 75.0−99.9 & 100 or more & Total \\
\hline Not HS. graduate H.S. graduate & 4207 & 3459 & 1389 & 539 & 367 & 9061 \\
\hline Some college & 4917 & 6850 & 5027 & 2637 & 2668 & 22000$ \\
\hline Bachelor's degree & 2807 & 5258 & 4678 & 3250 & 4074 & 20067 \\
\hline Beyond bach. deg. & 885
290 & 2094
829 & 2848 & 2581 & 5379 & 13787 \\
\hline Total & & 829 & 1274 & 1241 & 4188 & 7822 \\
\hline & & 1849 & 15216 & 10248 & 16676 & 73736 \\
\hline
\end{tabular} A] Compute column percentages.
أحسب الثسب المنوية للأعمد. B] What percentage of the heads of households did not graduate from high school? ما هي نسبة أرباب الأسر النين لم يتخرجوا من الثانوية العامة؟ C] What percentage of the households earning $50,000 or more were headed by a person having schooling beyond a bachelor's degree?
ما هي النسبة المنوية للاسر التي تكسب . 0 ألف دولار أو أكثر والتي يرأسها شخص حصل على تعليم يتجاوز رجة البكالوريوس؟ D] Construct percent frequency histograms of income for households headed by persons with a high school degree and for those headed by persons with a bachelor's degree. Is any relationship evident between household income and educational level? التي ير أسها أشخاص حاصلون على درجة البكالوربيرس. هل توجد علاقة واضحة بين دخل الأسرة و المستوى التُعلبيمي؟
Homework: HW \#12: Sections 9.1-9.3
Question 40, 9.3.11-T
HW Score: 71.53%,35.76 of 50 points
Part 1 of 6
Points: 0 of 1
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Question 40
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Question 44
Question 45 The following data lists the ages of a random selection of actresses when they won an award in the category of Best Actress, along with the ages of actors when they won in the category of Best Actor. The ages are matched according to the year that the awards were presented. Complete parts (a) and (b) below.
\begin{tabular}{lllllllllll}
\hline Actress (years) & 25 & 25 & 33 & 26 & 39 & 28 & 24 & 41 & 33 & 37 \\
\hline Actor (years) & 60 & 40 & 33 & 38 & 31 & 33 & 49 & 42 & 34 & 43 \\
\hline
\end{tabular}
a. Use the sample data with a 0.05 significance level to test the claim that for the population of ages of Best Actresses and Best Actors, the differences have a mean less than 0 (indicating that the Best Actresses are generally younger than Best Actors).
In this example, μd is the mean value of the differences d for the population of all pairs of data, where each individual difference d is defined as the actress's age minus the actor's age. What are the null and altermative hypotheses for the hypothesis test?
H0:μd□ year(s)
H1:μd□ years)
(Type integers or decimals. Do not round.) Help me solve this
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Graphs, Functions, and Sequences
Identifying proportional relationships in tables by calculating unit rates:... For each table, determine whether it shows that x and y are proportional.
If x and y are proportional, fill in the blank with a number in simplest form. Table 1
\begin{tabular}{|c|c|c|c|c|}
\hlinex & 6 & 14 & 20 & 24 \\
\hliney & 9 & 21 & 30 & 36 \\
\hline
\end{tabular} Proportional
y is □ times x
Not proportional Table 2
\begin{tabular}{|c|c|c|c|c|}
\hlinex & 12 & 16 & 20 & 24 \\
\hliney & 16 & 20 & 24 & 28 \\
\hline
\end{tabular}
Proportional
y is □ times x
Not proportional
1. Number of steps taken per day and number of kilometers walked per day. r=0.92 2. Temperature of a rubber band and distance the rubber band can stretch. r=0.84 3. Car weight and distance traveled using a full tank of gas. r=−0.86 4. Average fat intake per citizen of a country and average cancer rate of a country. r=0.73 5. Score on science exam and number of words written on the essay question. r=0.28 6. Average time spent listening to music per day and average time spent watching TV per day.
r=−0.17
Quiz 1 (10 points)
ID number: n subjects were chosen to study the length of time an adult rinses with a mouthwash in
relation to the manufacturer's recommended rinsing time. The random variable Xi represents the
length of time in seconds the ith subject has rinsed.
15 20 31 13 32 23 26 18 Compute the following: 1. mean 2. Median. Interpret it in words 3. standard deviation 4. the first quartile Coefficient of variation Skewness coefficient
QUESTION 4 (5,18)(4,13.5)(3,9) Given the graph of a linear function, identify the steps used to find the initial value. Check all that apply.
The initial value corresponds to the y value when x=0.
The initial value corresponds to the y value when x=1.
Find corresponding y values when x=6, x=7, and x=8. Then plot the points to finish the line.
Find corresponding y values when x=2, x=1, and x=0. Then plot the points to finish the line.
Find the rate of change using rise over run.
Two bikers rode at a constant speed on a 150-meter track. The data here show each biker's distance for a certain part of the race. Who won the race and by how much?
Student 1
Time (sec)
Distance (m)
4
40
6
60
8
80
10
100
Student 2
y
100
(10,105)
90
80
Distance (m)
70
(8,84)
60
50
(6,63)
40
(4,42)
30
20
10
x
2 4 6 8 10 12 14
Time (sec)
For the toolbar, press ALT
Reyna made a table showing how many sit-ups she could do
every 3 seconds. Use the table to match the characteristics of the
function with their real world meaning. Seconds | Sit-ups
------- | --------
0 | 0
3 | 2
6 | 4
9 | 6
12 | 8
\begin{tabular}{|c|c|c|}
\hlinex & 4 & 8 \\
\hlinef(x) & 11 & 6 \\
\hlinef′(x) & -4 & -3 \\
\hline
\end{tabular} The table above gives selected values for a differentiable and decreasing function f and its derivatives. Let g be the decreasing function given by g(x)=f(4x)−f(2x), where g(2)=f(8)−f(4)=−5. What is (g−1)′(−5) ?
4) In a pilot study we collected data on how many words 5 participants can remember. The data for this sample is 4, 5, 6, 7, and 8. In the general population, people can remember 8 words. What is the t value for this sample data?
QUESTION 5
The costs of different weights of onions sold at a grocery store are shown in the table below. What are the independent and dependent variables in this situation? Cost for Onions
\begin{tabular}{|c|c|}
\hline Weight of Onions (Pounds) & Total Cost \\
\hline 0.6 & $0.48 \\
\hline 1.3 & $1.04 \\
\hline 2.5 & $2.00 \\
\hline 3.7 & $2.96 \\
\hline
\end{tabular}
\begin{tabular}{|c|c|}
\hline Miles Traveled & \begin{tabular}{c}
Gallons of Gas \\
Used
\end{tabular} \\
\hline 48 & 1 \\
\hlinea & 2 \\
\hlineb & 3 \\
\hlinec & 4 \\
\hline
\end{tabular} A motorcycle can travel 48 miles for every gallon of gas used. Use the unit rate to complete the table for the miles traveled by a motorcycle.
a=b=c=49
50
96
Intro
Done
\begin{tabular}{|c|c|}
\hline Miles Traveled & \begin{tabular}{c}
Gallons of Gas \\
Used
\end{tabular} \\
\hline 30.5 & 1 \\
\hline 61 & 2 \\
\hlinex & 3 \\
\hline 122 & 4 \\
\hline
\end{tabular}
gas used.
Use proportional reasoning to find the value of x that completes the table showing this relationship.
x=
Done
x | y=−x+3 | y=2x+1
---|---|---|
0.5 | 2.5 | 2
0.6 | 2.4 | 2.2
0.7 | 2.3 | 2.4
0.8 | 2.2 | 2.6
0.9 | 2.1 | 2.8
1 | 2 | 3 c. Which two x-values will the solution be between? (1 point) d. Identify a reasonable approximation for the solution of this system. (2 points) 6. Find the solution to a system of inequalities. (6 points)
Question 7 of 16 (1 point)
Question Attempt: 1 of 1
Time Remaining tarks
"general anxiety" of an individual, with higher GAS scores corresponding to more anxiety. (Dr. Elbod's assessment of anxiety is based on a variety of measurements, both physiological and psychological.) y^=8.32−0.27x. This line, along with a scatter plot of the sample data, is shown below.
\begin{tabular}{|c|c|}
\hline GAS score, x & \begin{tabular}{c}
Sleep time, y \\
(in hours)
\end{tabular} \\
\hline 6.5 & 6.1 \\
\hline 7.0 & 6.5 \\
\hline 5.9 & 7.9 \\
\hline 1.0 & 6.9 \\
\hline 1.6 & 8.6 \\
\hline 4.0 & 6.6 \\
\hline 3.0 & 7.1 \\
\hline 3.6 & 8.2 \\
\hline 9.1 & 6.1 \\
\hline 3.5 & 7.5 \\
\hline 7.9 & 6.9 \\
\hline 2.0 & 8.3 \\
\hline 9.2 & 5.3 \\
\hline 8.1 & 5.4 \\
\hline 5.2 & 6.2 \\
\hline
\end{tabular}
Send data to calculator
Send data to Excel Based on the study's data and the regression line, answer the following.
(a) From the regression equation, what is the predicted sleep time (in hours) when the GAS score is 8.1 ? Round your answer to one or more decimal places.