Observed Frequencies |
Remedial English |
Not in Remedial English |
Total |
Normal |
22 |
187 |
209 |
ADD |
19 |
74 |
93 |
Total of the two categories |
41 |
261 |
302 |
My Question: How do you run the appropriate chi square test on this data in SPSS? I need to know how to set it up in SPSS and the step by step procedures. What goes in the data view/variable view and how do I run the test?
In: Math
Which of the following statements about the general exponential equation y = 600 (1.05)t is true? (Assume t is time in years, with t = 0 in 1950.) Check all that apply.
A)After 1950, each year the y-value is 1.05 times greater than the previous year.
B)The initial amount of 600 is increasing at a rate of 1.05% each year after 1950.
C)When t = 1, y is 105% of its original value, 600.
D)The initial amount of 600 is increasing at a rate of 5% each year after 1950.
In: Math
First National Bank employs three real estate appraisers whose job is to establish a property’s market value before the bank offers a mortgage to a prospective buyer. It is imperative that each appraiser values a property with no bias. Suppose First National Bank wishes to check the consistency of the recent values that its appraisers have established. The bank asked the three appraisers to value (in $1,000s) three different types of homes: a cape, a colonial, and a ranch. The results are shown in the accompanying table. (You may find it useful to reference the q table.)
Appraiser | |||
House Type | 1 | 2 | 3 |
Cape | 425 | 415 | 430 |
Colonial | 530 | 550 | 540 |
Ranch | 390 | 400 |
380 If average values differ by house type, use Tukey’s HSD method
at the 5% significance level to determine which averages differ.
(If the exact value for nT −
c is not found in the table, use the average of
corresponding upper & lower studentized range values. Negative
values should be indicated by a minus sign. Round your answers to 2
decimal places.) |
|
In: Math
Consider a refinery that produces three types of motor oil: Standard, Ex- tra, and Super. The selling prices are $9.00, $13.00, and $19.00 per barrel respectively. These oils can be made from three basic ingredients; crude oil, paraffin, and filler. The costs of the ingredients are $19.00, $9.00 and $11.00 per barrel, respectively. Company engineers have developed the following specifications for each oil Standard-60% paraffin, 40% filler Extra-at least 25% crude oil and no more than 45% paraffin Super-at least 50% crude oil and no more than 25% paraffin The CO2 emissions of Standard, Extra, and Super oils are 13.0, 11.8, and 8.0 units per barrel. With a supply capacity of 110, 90, and 70 thou- sand barrels per week for crude oil, paraffin, and filler, what should be blended in order to maximize profits as well as satisfy the requirements of the EPA to minimize the CO2 emissions from all the products of this industry? Solve the problem using the goal programming approach, if th goals are to have a profit greater than or equal to $5 per barrel and CO2 emissions less than or eaual to 10 units per barrel
In: Math
How does lowering the screening cutoff point effect sensitivity and specificity, Positive predictive value, and Negative Predictive Value of the test assuming prevalence stays the same? Why?
In: Math
You are a researcher who wants to know if there is a relationship between variable Y and variable X. You hypothesize that there will be a strong positive relationship between variable Y GPA and Variable X hours of sleep. After one semester, you select five students at random out of 200 students who have taken a survey and found that they do not get more than 5 hours of sleep per night. You select five more students at random from the same survey that indicates students getting at least seven hours of sleep per night. You want to see if there is a relationship between GPA and hours of sleep. Using a Pearson Product Correlation Coefficient statistic, determine the strength and direction of the relationship and determine if you can reject or fail to reject the HO:
Variable Y Variable X
2.5 5
3.4 8
2.0 4
2.3 4.5
1.6 3
3.2 6
2.8 7
3.5 7.5
4.0 6.5
3.8 7
In: Math
Heights of 10 year olds. Heights of 10 year olds, regardless of gender, closely follow a normal distribution with mean 55 inches and standard deviation 6 inches. Round all answers to two decimal places.
1. What is the probability that a randomly chosen 10 year old is shorter than 48 inches?
2. What is the probability that a randomly chosen 10 year old is between 50 and 51 inches?
3. If the shortest 10% of the class is considered very tall, what is the height cutoff for very tall? inches
4. What is the height of a 10 year old who is at the 34 th percentile? inches
In: Math
Using a random sample of n = 50, the sample mean is = 13.5. Suppose that the population standard deviation is σ=2.5.
Is the above statistical evidence sufficient to make the following claim μ ≠15:
?o: μ=15
??: μ ≠15
α = 0.05.
p value = 0
Interpret the results using the p value test.
Reject Ho
or
Do not reject Ho
In: Math
Most married couples have two or three personality preferences in common. A random sample of 375 married couples found that 134 had three preferences in common. Another random sample of 573 couples showed that 215 had two personality preferences in common. Let p1 be the population proportion of all married couples who have three personality preferences in common. Let p2 be the population proportion of all married couples who have two personality preferences in common.
(a) Find a 90% confidence interval for p1 – p2. (Round your answers to three decimal places.)
lower limit | |
upper limit |
In: Math
Crimini mushrooms are more common than white mushrooms, and they contain a high amount of copper, which is an essential element according to the U.S. Food and Drug Administration. A study was conducted to determine whether the weight of a mushroom is linearly related to the amount of copper it contains. A random sample of crimini mushrooms was obtained, and the weight (x, in grams) and the total copper content (y, in mg) was measured for each. You may assume that all of the assumptions for regression are valid. Please include three decimal places in all answers.The work for all of the parts will be submitted at the end of the question. The summry data is given below:
n = 30 SXX = 137.48 SYY = 5.778 SXY = 21.29 MSE = 0.0885 x̄ = 15.993
The line is
ŷ = -1.204 + 0.155 x
a) Find a 95% confidence interval for the true mean copper concentration when the weight of the mushroom is 18.2 g.
b)Find a 95% prediction interval for the true copper concentration when the weight of the mushroom is 18.2 g.
c) A value of 18.2 g is the size of an average Crimini mushroom. Is there any evidence to suggest that the you will get 1.9 mg of copper (the amount that is in one bar of dark chocolate) when you eat one average Crimini mushroom? Be sure to mention which interval, from above.
In: Math
Ten observations were selected from each of 3 populations and an analysis of variance was performed on the data. The following are the results:
Source of variation | Sum of squares | degrees of freedom | mean square | F |
Between treatments | 82.4 | |||
Within treatments (Error) | 158.4 | |||
Total |
A. Using alpha= .05, test to see if there is a significant difference among the means of the three populations.
B. If in part A you concluded that at least one mean is different from the others, determine which mean is different using LSD method. The three samples are (mean) X1=24.8, X2=23.4, X3=27.4.
In: Math
According to a study conducted for Gateway Computers, 59% of men and 70% of women say that weight is an extremely/very important factor in purchasing a laptop computer. Suppose this survey was conducted using 374 men and 481 women. Do these data show enough evidence to declare that a significantly higher proportion of women than men believe that weight is an extremely/very important factor in purchasing a laptop computer? Use alpha= 0.05.
Write the correct R commands for solving this problem. What is the p value? What is the statistical decision?
Use R command to construct a 90% confidence interval to estimate the difference in proportion of women and men believe that weight is an extremely/very important factor in purchasing a laptop computer.
In: Math
Child Health and Development Studies (CHDS) has been collecting data about expectant mothers in Oakland, CA since 1959. One of the measurements taken by CHDS is the weight increase (in pounds) for expectant mothers in the second trimester.
In a fictitious study, suppose that CHDS finds the average weight increase in the second trimester is 14 pounds. Suppose also that, in 2015, a random sample of 36 expectant mothers have mean weight increase of 16.1 pounds in the second trimester, with a standard deviation of 6.1 pounds.
A hypothesis test is done to see if there is evidence that weight increase in the second trimester is greater than 14 pounds.
Find the $p$-value for the hypothesis test.
The $p$-value should be rounded to 4 decimal places.
In: Math
In the Focus Problem at the beginning of this chapter, a study was described comparing the hatch ratios of wood duck nesting boxes. Group I nesting boxes were well separated from each other and well hidden by available brush. There were a total of 495 eggs in group I boxes, of which a field count showed about 268 hatched. Group II nesting boxes were placed in highly visible locations and grouped closely together. There were a total of 784 eggs in group II boxes, of which a field count showed about 272 hatched.
(a) Find a point estimate p̂1 for
p1, the proportion of eggs that hatch in group
I nest box placements. (Round your answer to three decimal
places.)
p̂1 =
Find a 95% confidence interval for p1. (Round
your answers to three decimal places.)
lower limit | |
upper limit |
(b) Find a point estimate p̂2 for
p2, the proportion of eggs that hatch in group
II nest box placements. (Round your answer to three decimal
places.)
p̂2 =
Find a 95% confidence interval for p2. (Round
your answers to three decimal places.)
lower limit | |
upper limit |
(c) Find a 95% confidence interval for p1 −
p2. (Round your answers to three decimal
places.)
lower limit | |
upper limit |
In: Math
The following data were obtained from a repeated-measures study comparing 3 treatment conditions. Use a repeated-measures ANOVA with a=.05 to determine whether there are significant mean differences among the three treatments (do all 4 steps of conducting a hypothesis test!!):
Person |
Treatment 1 |
Treatment 2 |
Treatment 3 |
Person Totals |
|
A |
0 |
2 |
4 |
P=6 |
N=15 |
B |
0 |
3 |
6 |
P=9 |
G=60 |
C |
3 |
7 |
8 |
P=18 |
|
D |
0 |
7 |
5 |
P=12 |
|
E |
2 |
6 |
7 |
P=15 |
|
M=1 |
M=5 |
M=6 |
|||
T=5 |
T=25 |
T=30 |
|||
SS=8 |
SS=22 |
SS=10 |
In: Math