Each year volunteers count the number of breeding horseshoe crabs on the beaches of Delaware Bay every year; here are data from 2011 and 2012. The measurement variable is number of horseshoe crabs, one nominal variable is 2011 vs. 2012, and the other nominal variable is the name of the beach. Each beach has one pair of observations of the measurement variable, one from 2011 and one from 2012. The biological question is whether the number of horseshoe crabs has gone up or down between 2011 and 2012. Here is a link to the data on the number of breeding horseshoe crabs on the beaches of Delaware Bay for the years 2011 and 2012. Calculate the difference in breeding horseshoe crab populations by subtracting the 2012 count of horseshoe crabs for each beach from the 2011 horseshoe crab counts for the same beaches. Plot the distribution of the differences in order to visually assess the distribution. It is EASY to plot the data in a histogram if you have the data analysis add-in installed on Microsoft Excel (Win Mac). From the Data Analysis window, select histogram, and then make sure Pareto (sorted histogram) and Chart Output are checked. Do you think the data are normally distributed, positively skewed, or negatively skewed? Would a two-sample t-test be an appropriate analysis for this data (yes or no)? Would a logarithmic transform be an appropriate way of transforming the data? Enter the number of your answer choice from the list below in the answer box 1. Yes, a logarithmic transform would result in normally distributed data. 2. No, a logarithmic transform is inappropriate because the data is already normally distributed. 3. No, a logarithmic transform is inappropriate because there are negative values which would result in undefined data points. Identify Ho and Ha for a paired t-test to determine if there is a difference in the number of breeding horseshoe crabs from 2011 to 2012. The mean difference between paired observations is zero. The mean difference between paired observations is not zero. Use the paired t-test function (=ttest(array1, array2, tails, type) to determine the if the two sets of measurements are correlated with each other. Report your answer to three decimal places. Do you fail to reject or reject the null hypothesis? Were the number of breeding horseshoe crabs the same or different between between the two years? Beach 2011 2012 Bennetts Pier 35282 21814 Big Stone 359350 83500 Broadkill 45705 13290 Cape Henlopen 49005 30150 Fortescue 68978 125190 Fowler 8700 4620 Gandys 18780 88926 Higbees 13622 1205 Highs 24936 29800 Kimbles 17620 53640 Kitts Hummock 117360 68400 Norburys Landi 102425 74552 North Bowers 59566 36790 North Cape Ma 32610 4350 Pickering 137250 110550 Pierces Point 38003 43435 Primehook 101300 20580 Reeds 62179 81503 Slaughter 203070 53940 South Bowers 135309 87055 South CSL 150656 112266 Ted Harvey 115090 90670 Townbank 44022 21942 Villas 56260 32140 Woodland 125 1260

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Each year volunteers count the number of breeding horseshoe crabs on the beaches of Delaware Bay every year; here are data from 2011 and 2012. The measurement variable is number of
horseshoe crabs, one nominal variable is 2011 vs. 2012, and the other nominal variable is the name of the beach. Each beach has one pair of observations of the measurement variable, one
from 2011 and one from 2012. The biological question is whether the number of horseshoe crabs has gone up or down between 2011 and 2012.
Here is a link to the data on the number of breeding horseshoe crabs on the beaches of Delaware Bay for the years 2011 and 2012.
Calculate the difference in breeding horseshoe crab populations by subtracting the 2012 count of horseshoe crabs for each beach from the 2011 horseshoe crab counts for the same beaches.
Plot the distribution of the differences in order to visually assess the distribution. It is EASY to plot the data in a histogram if you have the data analysis add-in installed on Microsoft Excel
(Win Mac). From the Data Analysis window, select histogram, and then make sure Pareto (sorted histogram) and Chart Output are checked.
Do you think the data are normally distributed, positively skewed, or negatively skewed?
Would a two-sample t-test be an appropriate analysis for this data (yes or no)?
Would a logarithmic transform be an appropriate way of transforming the data? Enter the number of your answer choice from the list below in the answer box
1. Yes, a logarithmic transform would result in normally distributed data.
2. No, a logarithmic transform is inappropriate because the data is already normally distributed.
3. No, a logarithmic transform is inappropriate because there are negative values which would result in undefined data points.
Identify Ho and Ha for a paired t-test to determine if there is a difference in the number of breeding horseshoe crabs from 2011 to 2012.
The mean difference between paired observations is zero.
The mean difference between paired observations is not zero.
Use the paired t-test function (=ttest(array1, array2, tails, type) to determine the if the two sets of measurements are correlated with each other.
Report your answer to three decimal places.
Do you fail to reject or reject the null hypothesis?
Were the number of breeding horseshoe crabs the same or different between between the two years?
Transcribed Image Text:Each year volunteers count the number of breeding horseshoe crabs on the beaches of Delaware Bay every year; here are data from 2011 and 2012. The measurement variable is number of horseshoe crabs, one nominal variable is 2011 vs. 2012, and the other nominal variable is the name of the beach. Each beach has one pair of observations of the measurement variable, one from 2011 and one from 2012. The biological question is whether the number of horseshoe crabs has gone up or down between 2011 and 2012. Here is a link to the data on the number of breeding horseshoe crabs on the beaches of Delaware Bay for the years 2011 and 2012. Calculate the difference in breeding horseshoe crab populations by subtracting the 2012 count of horseshoe crabs for each beach from the 2011 horseshoe crab counts for the same beaches. Plot the distribution of the differences in order to visually assess the distribution. It is EASY to plot the data in a histogram if you have the data analysis add-in installed on Microsoft Excel (Win Mac). From the Data Analysis window, select histogram, and then make sure Pareto (sorted histogram) and Chart Output are checked. Do you think the data are normally distributed, positively skewed, or negatively skewed? Would a two-sample t-test be an appropriate analysis for this data (yes or no)? Would a logarithmic transform be an appropriate way of transforming the data? Enter the number of your answer choice from the list below in the answer box 1. Yes, a logarithmic transform would result in normally distributed data. 2. No, a logarithmic transform is inappropriate because the data is already normally distributed. 3. No, a logarithmic transform is inappropriate because there are negative values which would result in undefined data points. Identify Ho and Ha for a paired t-test to determine if there is a difference in the number of breeding horseshoe crabs from 2011 to 2012. The mean difference between paired observations is zero. The mean difference between paired observations is not zero. Use the paired t-test function (=ttest(array1, array2, tails, type) to determine the if the two sets of measurements are correlated with each other. Report your answer to three decimal places. Do you fail to reject or reject the null hypothesis? Were the number of breeding horseshoe crabs the same or different between between the two years?
Beach
2011
2012
Bennetts Pier
35282
21814
Big Stone
359350
83500
Broadkill
45705
13290
Cape Henlopen
49005
30150
Fortescue
68978
125190
Fowler
8700
4620
Gandys
18780
88926
Higbees
13622
1205
Highs
24936
29800
Kimbles
17620
53640
Kitts Hummock
117360
68400
Norburys Landi
102425
74552
North Bowers
59566
36790
North Cape Ma
32610
4350
Pickering
137250
110550
Pierces Point
38003
43435
Primehook
101300
20580
Reeds
62179
81503
Slaughter
203070
53940
South Bowers
135309
87055
South CSL
150656
112266
Ted Harvey
115090
90670
Townbank
44022
21942
Villas
56260
32140
Woodland
125
1260
Transcribed Image Text:Beach 2011 2012 Bennetts Pier 35282 21814 Big Stone 359350 83500 Broadkill 45705 13290 Cape Henlopen 49005 30150 Fortescue 68978 125190 Fowler 8700 4620 Gandys 18780 88926 Higbees 13622 1205 Highs 24936 29800 Kimbles 17620 53640 Kitts Hummock 117360 68400 Norburys Landi 102425 74552 North Bowers 59566 36790 North Cape Ma 32610 4350 Pickering 137250 110550 Pierces Point 38003 43435 Primehook 101300 20580 Reeds 62179 81503 Slaughter 203070 53940 South Bowers 135309 87055 South CSL 150656 112266 Ted Harvey 115090 90670 Townbank 44022 21942 Villas 56260 32140 Woodland 125 1260
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"Use the paired t-test function (=ttest(array1, array2, tails, type) to determine the if the two sets of measurements are correlated with each other."

 

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