As part of a study of wheat maturation, an agronomist selected a
sample of wheat plants at random from a field plot. For each plant,
the agronomist measured the moisture content from two locations:
one from the central portion and one from the top portion of the
wheat head. The agronomist hypothesizes that the central portion of
the wheat head has more moisture than the top portion. What can the
agronomist conclude with α = 0.01? The moisture content data are
below.
central | top |
---|---|
62.7 63.6 60.9 63.1 62.7 63.7 62.5 |
61.7 62.7 60.2 62.5 61.6 62.8 62.3 |
a) What is the appropriate test statistic?
---Select--- na, z-test, One-Sample t-test, Independent-Samples
t-test, Related-Samples t-test
b)
Condition 1:
---Select--- top portion wheat maturation moisture content wheat
head central portion
Condition 2:
---Select--- top portion wheat maturation moisture content wheat
head central portion
c) Compute the appropriate test statistic(s) to
make a decision about H0.
critical value = ; test statistic =
Decision: ---Select--- Reject H0, Fail to reject
H0
d) If appropriate, compute the CI. If not
appropriate, input "na" for both spaces below. (Please say if
"na")
[ , ]
e) Compute the corresponding effect size(s) and
indicate magnitude(s).
If not appropriate, input and/or select "na" below.
d = ; ---Select--- na, trivial effect, small
effect, medium effect, large effect
r2 = ; ---Select--- na, trivial
effect, small effect, medium effect, large effect
f) Make an interpretation based on the results.
(select one)
-The central portion of the wheat head had significantly more moisture than the top portion.
-The central portion of the wheat head had significantly less moisture than the top portion.
-There was no significant moisture difference between the central and top portion of the wheat head
In: Math
Quantitative noninvasive techniques are needed for routinely assessing symptoms of peripheral neuropathies, such as carpal tunnel syndrome (CTS). An article reported on a test that involved sensing a tiny gap in an otherwise smooth surface by probing with a finger; this functionally resembles many work-related tactile activities, such as detecting scratches or surface defects. When finger probing was not allowed, the sample average gap detection threshold for m = 7 normal subjects was 1.85 mm, and the sample standard deviation was 0.57; for n = 11 CTS subjects, the sample mean and sample standard deviation were 2.47 and 0.85, respectively. Does this data suggest that the true average gap detection threshold for CTS subjects exceeds that for normal subjects? State and test the relevant hypotheses using a significance level of 0.01. (Use μ1 for normal subjects and μ2 for CTS subjects.)
Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)
t | = | |
P-value | = |
In: Math
Many freeways have service (or logo) signs that give information on attractions, camping, lodging, food, and gas services prior to off-ramps. These signs typically do not provide information on distances. An article reported that in one investigation, six sites along interstate highways where service signs are posted were selected. For each site, crash data was obtained for a three-year period before distance information was added to the service signs and for a one-year period afterward. The number of crashes per year before and after the sign changes were as follows.
Before: | 15 | 23 | 65 | 121 | 66 | 65 |
After: | 16 | 21 | 43 | 83 | 79 | 74 |
a)The article included the statement "A paired t test
was performed to determine whether there was any change in the mean
number of crashes before and after the addition of distance
information on the signs." Carry out such a test. [Note:
The relevant normal probability plot shows a substantial linear
pattern.]
State and test the appropriate hypotheses. (Use
α = 0.05.)
Calculate the test statistic and P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)
t | = | |
P-value | = |
b)If a seventh site were to be randomly selected among locations bearing service signs, between what values would you predict the difference in number of crashes to lie? (Use a 95% prediction interval. Round your answers to two decimal places.)
In: Math
A technician compares repair costs for two types of microwave ovens (type I and type II). He believes that the repair cost for type I ovens is greater than the repair cost for type II ovens. A sample of 5959 type I ovens has a mean repair cost of $73.27$73.27, with a standard deviation of $10.76$10.76. A sample of 4747 type II ovens has a mean repair cost of $69.22$69.22, with a standard deviation of $23.21$23.21. Conduct a hypothesis test of the technician's claim at the 0.050.05 level of significance. Let μ1μ1 be the true mean repair cost for type I ovens and μ2μ2 be the true mean repair cost for type II ovens.
Step 2 of 4 :
Compute the value of the test statistic. Round your answer to two decimal places.
Step 3 of 4: Determine the decision rule for rejecting the null hypothesis H0. Round the numerical portion of your answer to two decimal places
Step 4 of 4: Make the decision for the hypothesis test. Fail or reject to fail.
In: Math
Consider the data.
xi |
3 | 12 | 6 | 20 | 14 |
---|---|---|---|---|---|
yi |
55 | 35 | 45 | 10 | 15 |
The estimated regression equation for these data is ŷ = 62.25 − 2.75x.
(a) Compute SSE, SST, and SSR using equations SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2.
SSE=
SST=
SSR=
(b) Compute the coefficient of determination r2.(Round your answer to three decimal places.)
r2 =
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) Chose one of the following.
1.The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line.
2.The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the least squares line.
3.The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.
4.The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line.
(c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)
In: Math
A plant physiologist investigated the effect of flooding on root metabolism in two tree
species: flood-tolerant river birch and the intolerant European birch. Four seedlings of
each species were flooded for one day, and four were used as controls. The concentration
of adenosine triphosphate (ATP) in the roots of each plant was measured. The data (nmol
ATP per mg tissue) as shown in the table.
River birch European Birch
Flooded Control Flooded Control
1.45 |
1.70 | 0.21 | 1.34 | |
1.19 | 2.04 | 0.58 | 0.99 | |
1.05 | 1.49 | 0.11 | 1.17 | |
1.07 | 1.91 | 0.27 | 1.30 | |
Mean | 1.19 | 1.785 | 0.2925 | 1.20 |
For these data, SS(species of birch)=2.19781, SS(flooding)=2.25751, SS(interaction)=0.097656,
and SS(within)=0.47438.
i. Construct the ANOVA table, include p-values.
iii. What is the F test statistic and its degrees of freedom for testing that species has no
effect on ATP concentration?
In: Math
Consider the daily percent changes of McDonald’s stock price and those of the Dow
Jones Industrial Average for trading days in the months of July and August 1987.
Data can be found in the Excel file S4.XLSX (Mc-Dow) in the Excel directory.
a. Draw a scatterplot of McDonald’s daily percent changes against the Dow Jones
percent changes.
b. Describe the relationship you see in this scatterplot.
c. Find the correlation between these percent changes. Does this agree with your
impression of the scatterplot?
d. Find the coefficient of determination (you may just square the correlation).
Interpret this number as “variation explained”. In financial terms, it represents
the proportion of non-diversifiable risk in McDonald’s. For example, if it were
100%, McDonald’s stock would track the market perfectly, and diversification
would introduce nothing new.
e. Find the proportion of diversifiable risk. This is just 1 - R2 (or 100% minus the
percentage of non-diversifiable risk). This indicates the extent to which you
can diversify away the risk of McDonald's stock by investing part of your
portfolio in the Dow Jones Industrial stocks.
f. Find the regression equation to predict the percent change in McDonald's stock
from the percent change in the Dow Jones Index. Identify the stock's so-called
beta, a measure used by market analysts, which is equal to the slope of this
line. According to the capital asset pricing model, stocks with large beta values
tend to give larger expected returns (on average, over time) than stocks with
smaller betas.
g. Find the 95% confidence interval for the slope coefficient.
h. Test at the 5% level to see whether or not the daily percent changes of
McDonald's and of the Dow Jones Index are significantly associated.
i. Test at the 5% level to see whether the beta of McDonald's is significantly
different from 1, which represents the beta of a highly diversified portfolio
McDonald’s stock vs Dow Jones | |
Dow Jones | McDonald’s |
0.47 | 1.12 |
1.41 | -0.29 |
0.70 | 0.83 |
0.69 | 0.58 |
-0.69 | -0.52 |
-1.38 | 0.20 |
-2.34 | -0.12 |
1.44 | 1.16 |
-0.24 | 0.10 |
0.47 | 0.53 |
-1.18 | 0.52 |
-1.19 | -0.89 |
0.72 | -0.80 |
0.72 | 0.09 |
0.95 | 0.07 |
0.94 | 0.54 |
0.93 | 0.35 |
0.92 | 1.04 |
0.92 | 0.78 |
0.45 | 1.10 |
0.23 | 0.18 |
-1.35 | -0.58 |
-1.14 | -0.41 |
2.08 | 0.78 |
3.17 | 1.07 |
-0.66 | -0.09 |
1.99 | 1.69 |
3.03 | 1.69 |
-0.84 | -0.42 |
1.48 | 0.83 |
-0.63 | -0.23 |
2.31 | 0.56 |
-0.21 | -1.70 |
-2.06 | 0.42 |
0.84 | 1.54 |
0.00 | 0.10 |
-2.08 | -0.46 |
2.34 | 0.94 |
-0.21 | 0.76 |
-1.67 | -0.99 |
-2.33 | -1.33 |
1.08 | 0.89 |
In: Math
In: Math
A toll-free phone number is available from 9 a.m. to 9 p.m. for your customers to register complaints about a product purchased from your company. Past history indicates that an average of 1.0 calls are received per minute. Complete parts (a)through (c).
A. what is the probability that during a 1 min period zero phone calls will be received?
B. what is the probability that during a 1 min period three or more phone calls will be received?
C. what is the maximum number of phone calls that will be received in a 1 min period 99.99% of the time?
In: Math
30. In an effort to make a healthier product, the Oriental Spice Sauce company has reduced the amount of sodium in their product to 800mg. In addition, the standard deviation of the amount of sodium should be 80. To make sure this new product continues to meet the standard, a random sample of 24 bottles is taken, and the standard deviation for the sample was 120.7812. Is there evidence at α=0.025 that the standard deviation of the sodium content exceeds the desired level? Assume the population is normally distributed.
Step 1 of 5: State the null and alternative hypotheses. Round to four decimal places when necessary.
H0:
Ha:
Step 2 of 5: Determine the critical value(s) of the test statistic. If the test is two-tailed, separate the values with a comma. Round your answer to three decimal places.
Step 3 of 5: Determine the value of the test statistic. Round your answer to three decimal places.
Step 4 of 5: Make the decision.
A. Reject Null Hypothesis
B. Fail to Reject Null Hypothesis
Step 5 of 5: What is the conclusion?
A. There is sufficient evidence to show that the standard deviation of the sodium content exceeds the desired level.
B. There is not sufficient evidence to show that the standard deviation of the sodium content exceeds the desired level.
In: Math
CASE STUDY /big 4 Consultants has been appointed by a leading group in hotel industry to prepare feasibility report for opening a five-star hotel in Ras al Khaima. The group had been most successful one in the hotel industry and had always kept its eyes open for new opportunities.
In view of the very fast industrial growth in the city of Ras al Khaima, the city had attracted the attention of the group. It is historically known as Julfar, is one of the seven emirates that make up the United Arab Emirates (UAE). Its name could be taken to mean "headland of the small huts", which can be attributed to the indigenous buildings that existed along the coast. The Emirate is in the northern part of the UAE, bordering Oman’s exclave of Musandum. RAK, apart from being a developing city, has added advantage of pleasant weather and several places of tourist attraction in the neighborhood. Moreover, the closeness to Dubai and Abudhabi, a city of international stature, has made it very easily accessible to international tourists.
For this Consultancy, this was the first time in this area that an assignment concerning hotel industry had been received. They, however, soon realized that the assignment was not as simple as it appeared to be in the first place. The feasibility of such a hotel would depend essentially on two factors. Businessman visiting the city for work would constitute one segment of the market, while tourists would constitute the other. Further, the tourists could be from UAE or foreigners. The success of such a hotel would also depend upon the relative attraction of other tourist centres in the vicinity. Further, it was necessary to estimate fluctuations in demand for hotel accommodation so that attractive discounts could be offered during the off-season for business conferences, executive developmental programmes, etc.
The consultants realized that they would have to undertake a market research on a national scale to assess the tourist potential of the city. They would also have to survey the foreign tourists to estimate one of the most important segments of the market. They wondered whether such a survey will have to extend over a period of one full year to completely take into account the seasonal variations in tourists’ traffic. Moreover, they were undecided about the manner in which survey should be conducted. The company also feared that in absence of an accurate definition of the problem, they may land up surveying the complete tourist market in UAE rather than studying feasibility of a hotel in RAK.
Thus, the problem appeared well defined and that they were concerned as the preliminary report explaining methodology of the research and the questionnaires to be used to be submitted to the client along with the estimate of expenses within one month.
QUESTIONS
1. Apply your ideas in defining the problem of assessing feasibility of hotel in RAK so as
to help designing the survey.
2. It is important to plan a survey for collecting information on expected demand for
hotel space. Illustrate.
3. Being the coordinator of this research at Big 4 Consultants, explain various steps you
would suggest to your research team in preparing the report to the Hotel management.
In: Math
A random sample of 880 births included 433 boys. Use a 0.10 significance level to test the claim that 50.8% of newborn babies are boys. Do the results support the belief that 50.8% of newborn babies are boys?
In: Math
The data below are the average monthly temperatures, in °F, and the monthly natural gas consumption, in ccf, for a household in northwestern Pennsylvania.
a.)Test the significance of the correlation coefficient using α = 0.05 and the claim ρ < 0. Identify the claim, state the null and alternative hypotheses, find the critical value, find the standardized test statistic, make a decision on the null hypothesis (you may use a P-Value instead of the standardized test statistic), write an interpretation statement on the decision
b.) Find the equation of the regression line for the given data
Temperature |
47 |
35 |
21 |
27 |
39 |
48 |
61 |
65 |
70 |
|||
Consumption |
34 |
169 |
248 |
134 |
137 |
100 |
19 |
34 |
12 |
In: Math
Following are the number of miles traveled for 30 randomly selected business flights within the United States during 1999.
1095, 925, 1656, 1605, 1503, 1928, 2030, 1418, 500, 1248,
2047, 1027, 1962, 1027, 1197, 1928, 874, 1367, 1129, 1401,
874, 602, 1503, 1469, 636, 1503, 925, 1384, 874, 704
a) Use the data to obtain a point estimate for the population
mean number of miles traveled per business flight, μ, in
1999.
Note: The sum of the data is 38341.
b) Determine a 95.44% confidence interval for the population mean number of miles traveled per business flight in 1999. Assume that σ=450 miles. Confidence interval: ( , ).
c) Must the number of miles traveled per business flight in 1999 be exactly normally distributed for the confidence interval that you obtained in part (b) to be approximately correct?
d) What theorem helped you answer part (c)?
In: Math