We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here
worker wages los size 1 46.3791 34 Large 2 37.3643 28 Small 3 58.9662 89 Small 4 47.4511 24 Small 5 98.45 90 Large 6 51.3039 205 Small 7 78.8469 52 Large 8 48.6907 47 Large 9 52.1521 39 Large 10 76.5752 147 Small 11 64.5643 32 Large 12 47.7774 28 Small 13 39.4675 16 Small 14 75.3756 25 Large 15 42.7038 95 Large 16 37.3256 21 Large 17 47.6141 24 Large 18 39.0678 64 Small 19 41.587 34 Large 20 64.102 50 Large 21 72.0744 79 Large 22 69.4551 99 Small 23 49.7729 57 Large 24 46.8856 72 Small 25 62.1589 38 Large 26 51.3016 106 Small 27 38.2666 135 Small 28 46.6623 17 Large 29 41.256 44 Large 30 50.9605 40 Large 31 52.8366 53 Small 32 47.635 74 Large 33 61.0205 79 Large 34 62.3736 82 Small 35 38.8286 52 Large 36 56.931 31 Large 37 72.1109 20 Large 38 70.1955 87 Small 39 70.9977 84 Large 40 60.4625 50 Small 41 69.0306 86 Small 42 47.8044 17 Small 43 66.7418 128 Large 44 40.8045 99 Small 45 56.4676 95 Large 46 82.3129 37 Small 47 49.438 102 Large 48 60.0954 28 Large 49 49.7582 27 Small 50 70.0533 155 Large 51 68.4439 56 Large 52 43.1397 42 Large 53 37.8087 154 Large 54 39.9629 102 Small 55 50.4422 42 Small 56 41.7852 162 Large 57 52.8019 63 Small 58 85.8806 119 Large 59 50.1035 25 Small 60 77.1412 122 Large
is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.
(a) Plot wages versus LOS. Consider the relationship and whether
or not linear regression might be appropriate. (Do this on paper.
Your instructor may ask you to turn in this graph.)
(b) Find the least-squares line. Summarize the significance test
for the slope. What do you conclude?
| Wages = | ___+___ LOS |
| t = | |
| P = |
(c) State carefully what the slope tells you about the relationship
between wages and length of service.
(d) Give a 95% confidence interval for the slope.
(___,___)
In: Statistics and Probability
We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here (data297.dat) is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.
(a) Plot wages versus LOS. Consider the relationship and whether
or not linear regression might be appropriate. (Do this on paper.
Your instructor may ask you to turn in this graph.)
(b) Find the least-squares line. Summarize the significance test
for the slope. What do you conclude?
| Wages = | + LOS |
| t = | |
| P = |
(c) State carefully what the slope tells you about the relationship
between wages and length of service.
This answer has not been graded yet.
(d) Give a 95% confidence interval for the slope.
( , )
data:
worker wages los size 1 52.5003 32 Large 2 42.9112 20 Small 3 44.8013 22 Small 4 47.6345 66 Small 5 57.4056 47 Large 6 42.1011 85 Small 7 80.6868 145 Large 8 61.5946 110 Large 9 43.4947 114 Large 10 46.5104 100 Small 11 70.3836 38 Large 12 59.0304 67 Small 13 48.4712 138 Small 14 42.8046 98 Large 15 53.1633 57 Large 16 65.5307 38 Large 17 76.2445 52 Large 18 44.5201 33 Small 19 41.7859 46 Large 20 67.3025 51 Large 21 56.3646 97 Large 22 45.8435 62 Small 23 37.2773 18 Large 24 55.9512 65 Small 25 53.8214 75 Large 26 60.0009 62 Small 27 50.1449 49 Small 28 40.6285 88 Large 29 46.7619 16 Large 30 38.1294 57 Large 31 38.2563 53 Small 32 56.5517 23 Large 33 46.8022 73 Large 34 53.0068 27 Small 35 39.6801 33 Large 36 54.6719 193 Large 37 55.4562 44 Large 38 40.0471 90 Small 39 38.2987 134 Large 40 38.1887 137 Small 41 62.77 66 Small 42 57.0192 37 Small 43 54.1235 122 Large 44 38.6294 38 Small 45 73.5348 167 Large 46 41.8152 92 Small 47 54.049 90 Large 48 51.0795 25 Large 49 60.5716 68 Small 50 57.972 62 Large 51 52.8388 112 Large 52 47.4715 66 Large 53 61.9632 74 Large 54 65.7441 30 Small 55 41.1799 46 Small 56 49.2086 124 Large 57 41.9043 46 Small 58 53.8185 31 Large 59 52.6962 98 Small 60 57.4416 109 Large
In: Statistics and Probability
We assume that our wages will increase as we gain experience and become more valuable to our employers. Wages also increase because of inflation. By examining a sample of employees at a given point in time, we can look at part of the picture. How does length of service (LOS) relate to wages? The data here (data323.dat) is the LOS in months and wages for 60 women who work in Indiana banks. Wages are yearly total income divided by the number of weeks worked. We have multiplied wages by a constant for reasons of confidentiality.
(a) Plot wages versus LOS. Consider the relationship and whether
or not linear regression might be appropriate. (Do this on paper.
Your instructor may ask you to turn in this graph.)
(b) Find the least-squares line. Summarize the significance test
for the slope. What do you conclude?
| Wages = | + LOS |
| t = | |
| P = |
(c) State carefully what the slope tells you about the relationship
between wages and length of service.
(d) Give a 95% confidence interval for the slope.
here is the data set :
worker wages los size 1 80.7641 70 Large 2 47.6952 153 Small 3 68.1211 140 Small 4 42.5447 95 Small 5 48.7555 67 Large 6 41.3497 57 Small 7 53.8695 86 Large 8 55.5691 22 Large 9 42.954 113 Large 10 38.8381 66 Small 11 62.0195 32 Large 12 49.806 57 Small 13 52.9859 15 Small 14 40.9619 77 Large 15 56.5876 60 Large 16 45.531 30 Large 17 47.4383 96 Large 18 44.2084 60 Small 19 51.6572 144 Large 20 70.5038 131 Large 21 38.2412 41 Large 22 38.7429 59 Small 23 46.3128 94 Large 24 68.4899 63 Small 25 71.0578 56 Large 26 51.4918 18 Small 27 38.1531 100 Small 28 54.2316 18 Large 29 45.8801 52 Large 30 49.1423 102 Large 31 45.3795 88 Small 32 70.3286 18 Large 33 51.6134 100 Large 34 83.4615 91 Small 35 37.6516 39 Large 36 56.9919 27 Large 37 50.6129 24 Large 38 47.5097 60 Small 39 44.0107 96 Large 40 39.905 92 Small 41 61.5252 45 Small 42 38.3112 110 Small 43 43.332 49 Large 44 47.0086 20 Small 45 37.0101 53 Large 46 70.9395 131 Small 47 42.971 26 Large 48 40.4821 107 Large 49 43.8952 63 Small 50 57.4178 51 Large 51 57.7934 43 Large 52 70.8782 44 Large 53 40.4416 53 Large 54 41.6311 30 Small 55 47.348 66 Small 56 45.9943 74 Large 57 45.7749 25 Small 58 53.1182 56 Large 59 47.113 55 Small 60 46.3262 19 Large
In: Statistics and Probability
You borrow $250,000 to buy a home. The terms of the loan are as follows: 30-year mortgage loan at a rate of 4.50 percent with monthly payments. What percentage of your first month's payment goes toward interest?
| A. |
67 percent |
|
| B. |
43 percent |
|
| C. |
74 percent |
|
| D. |
89 percent |
|
| E. |
58 percent |
In: Finance
The mean of sample A is significantly different than the mean of sample B. Sample A: 59 46 74 62 87 73 Sample B: 53 67 81 57 93 79 Use a two-tailed t-test of independent samples for the above hypothesis and data. What is the p-value? (Answer to 3 decimal places)
In: Statistics and Probability
1. A researcher wishes to estimate the proportion of left-handers among a certain population. In a random sample of 900 people from the population, 74% are left-handed.
a. Find the margin of error for the 95% confidence interval for the population proportion of the left-handers.
b. Find the 95% confidence interval for the population proportion of the left-handers to four decimal places.
In: Statistics and Probability
Find the measures of center for following.
| Data | Frequency |
|---|---|
| 40 - 44 | 10 |
| 45 - 49 | 23 |
| 50 - 54 | 12 |
| 55 - 59 | 10 |
| 60 - 64 | 5 |
| 65 - 69 | 4 |
| 70 - 74 | 2 |
| 75 - 79 | 0 |
| 80 - 84 | 1 |
mode =
median =
mean = (round to 4 decimal places)
In: Statistics and Probability
The score of a course out of 100 in Winter of 10 students are 48, 92, 47, 44, 94, 18, 95, 67, 74, 64
a. Calculate Q1, Q3 and IQR of the data.
b. Find the mean, median and standard deviation
c. Determine whether the smallest value of this data set is an outlier.
d. Comment the shape of the distribution.
In: Statistics and Probability
(Need Ans ASAP PLEASE) You have been hired to test whether the demand for a product that your client produces varies between two demographic markets – the Urban and Rural markets.
As such, in each market, you run a short survey that gauges customers demand for your product and assigns them to one of three categories – (i) High (ii) Medium or (iii) Low.
You survey 70 people in the “Urban” market and find that their demand falls into the following “buckets”
High 32
Medium 20
Low 18
You survey 30 people in the “Rural” market time. Their demand for the product its reflected below.
High 8
Medium 10
Low 12
The Null hypothesis that you are asked to test is that "the demand for the product is INDEPENDENT of the whether the market is Urban or Rural.”
Using the critical values for the 5% and 1% levels of the Chi-Square Distribution from your text, which of the following statements is true
|
We cannot reject the null hypothesis at the 5% or 1% level |
|
|
We can reject the null hypothesis at both the 5% and the 1% levels. |
|
|
We can reject the null hypothesis at the 5% level. |
|
|
We can reject the null hypothesis at the 1% level. |
In: Statistics and Probability
A spring has a natural length of 24 cm. If a 27-N force is required to keep it stretched to a length of 30 cm, how much work W is required to stretch it from 24 cm to 27 cm? Round your answer to two decimal places. W = J
In: Math