The data in this question provides list of new cases and new death related to COVID-19 in London for the month of June 2020.a. Analysis of New cases:i. Use Excel to construct a frequency table, frequency histogram, and ogive for the new cases use the bin values provided. What can you observe about the data from the frequency distribution? How would you characterize the shape of the distribution?ii. Use Excel to find mean, median, mode, range, and standard deviation for the new Cases of COVID-19 in London for the Month of June.iii. Based on part i and ii, describe the distribution of new cases in June 2020?b. Analysis of new death count:i. Use Excel to construct a frequency table, frequency histogram, and ogive for the death count use the bin values provided. What can you observe about the data from the frequency distribution? How would you characterize the shape of the distribution?ii. Use Excel to find mean, median, mode, range, and standard deviation for the death count of COVID-19 in London for the Month of June EditViewInsertFormatToolsDataWindowHelpExcelFileRSMT 1000 Project Data - Fall 2020AutoSaveOFF4 ShareCommentFormulasDataReviewView Tell meHomeInsertDrawPage LayoutConditional FormattingCalibri (Body)11A AFormat as TableCellsEditingIdeasSensitivityA.AlignmentNumberCell StylesPasteBIUVH6X fxH.A.B.Bin Values for #of deathBin Value for new casesCummulative (Death)2276Cummulative (New)X increaseNew DeathDateNew Cases150282631.510102.2020-06-01418200172293446287091.6152020-06-022312250290471.219202020-06-03338300294031.2452357252020-06-04356350297471.21523726.2020-06-0S34440030352407455302021.5352020-06-062426450306171.419402020-06-074155000.7924245024330860456.2020-06-082464310900.7414102020-06-092302485313410.8121112020-06-102512487315440.652.122020-06-112032498317260.5711132020-06-121822507319920.846.142020-06-132662519321890.6212152020-06-141972527323700.568.162020-06-151812538325540.5711172020-06-1618425500.581219032744182020-06-172553329170.53192020-06-181732564330950.5411202020-06-191782595333010.6231212020-06-202060.531126062020-06-2117538476222609336370.48232020-06-221612619338530,6410242020-06-232160,4812263116334016252020-06-242641342050.5610262020-06-251892644111343160.32272020-06-262652160344760.47282020-06-272658178346540.52292020-06-2B2665257349110.74302020-06-292672,350680.45312020-06-30157323334353637ONa m m mm4,

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MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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The data in this question provides list of new cases and new death related to COVID-19 in London for the month of June 2020.

a. Analysis of New cases:

i. Use Excel to construct a frequency table, frequency histogram, and ogive for the new cases use the bin values provided. What can you observe about the data from the frequency distribution? How would you characterize the shape of the distribution?

ii. Use Excel to find mean, median, mode, range, and standard deviation for the new Cases of COVID-19 in London for the Month of June.

iii. Based on part i and ii, describe the distribution of new cases in June 2020?

b. Analysis of new death count:

i. Use Excel to construct a frequency table, frequency histogram, and ogive for the death count use the bin values provided. What can you observe about the data from the frequency distribution? How would you characterize the shape of the distribution?

ii. Use Excel to find mean, median, mode, range, and standard deviation for the death count of COVID-19 in London for the Month of June

Edit
View
Insert
Format
Tools
Data
Window
Help
Excel
File
RSMT 1000 Project Data - Fall 2020
AutoSave
OFF
4 Share
Comment
Formulas
Data
Review
View Tell me
Home
Insert
Draw
Page Layout
Conditional Formatting
Calibri (Body)
11
A A
Format as Table
Cells
Editing
Ideas
Sensitivity
A.
Alignment
Number
Cell Styles
Paste
BIUV
H6
X fx
H.
A.
B.
Bin Values for #of death
Bin Value for new cases
Cummulative (Death)
2276
Cummulative (New)
X increase
New Death
Date
New Cases
150
28263
1.5
10
10
2.
2020-06-01
418
200
17
2293
446
28709
1.6
15
2020-06-02
2312
250
29047
1.2
19
20
2020-06-03
338
300
29403
1.2
45
2357
25
2020-06-04
356
350
29747
1.2
15
2372
6.
2020-06-0S
344
400
30
35
2407
455
30202
1.5
35
2020-06-06
2426
450
30617
1.4
19
40
2020-06-07
415
500
0.79
24
2450
243
30860
45
6.
2020-06-08
2464
31090
0.74
14
10
2020-06-09
230
2485
31341
0.81
21
11
2020-06-10
251
2487
31544
0.65
2.
12
2020-06-11
203
2498
31726
0.57
11
13
2020-06-12
182
2507
31992
0.84
6.
14
2020-06-13
266
2519
32189
0.62
12
15
2020-06-14
197
2527
32370
0.56
8.
16
2020-06-15
181
2538
32554
0.57
11
17
2020-06-16
184
2550
0.58
12
190
32744
18
2020-06-17
2553
32917
0.53
19
2020-06-18
173
2564
33095
0.54
11
20
2020-06-19
178
2595
33301
0.62
31
21
2020-06-20
206
0.53
11
2606
2020-06-21
175
38476
22
2609
33637
0.48
23
2020-06-22
161
2619
33853
0,64
10
24
2020-06-23
216
0,48
12
2631
163
34016
25
2020-06-24
2641
34205
0.56
10
26
2020-06-25
189
2644
111
34316
0.32
27
2020-06-26
2652
160
34476
0.47
28
2020-06-27
2658
178
34654
0.52
29
2020-06-2B
2665
257
34911
0.74
30
2020-06-29
2672,
35068
0.45
31
2020-06-30
157
32
33
34
35
36
37
ON
a m m mm
4,

Definition Definition Measure of central tendency that is the value that occurs most frequently in a data set. A data set may have more than one mode if multiple categories repeat an equal number of times. For example, in a data set with five item—3, 5, 5, 29, 473—the mode is 5 because it occurs twice and no other value occurs more than once. On a histogram or bar chart, the element with the highest bar represents the mode. Therefore, the mode is sometimes considered the most popular option. The mode is useful for nominal or categorical data (e.g., the most common color car that users purchase), but it is problematic for continuous data because it is more likely not to have any value that is more frequent than the other.

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