Questions
Purchase-Related Transactions Journalize entries for the following related transactions of Lilly Heating & Air Company: Purchased...

Purchase-Related Transactions

Journalize entries for the following related transactions of Lilly Heating & Air Company:

  1. Purchased $23,000 of merchandise from Schell Co. on account, terms 1/10, n/30.
  2. Paid the amount owed on the The bill that the seller sends to the buyer.invoice within the discount period.
  3. Discovered that $4,600 before purchases discount of the merchandise was defective and returned items, receiving credit.
  4. Purchased $3,800 of merchandise from Schell Co. on account, terms n/30.
  5. Received a check for the balance owed from the return in (c), after deducting for the purchase in (d).
a. Inventory
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
Accounts Payable-Schell Co.
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
b. Accounts Payable-Schell Co.
  • Accounts Payable-Schell Co.
  • Cost of Merchandise Sold
  • Inventory
  • Purchases
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
Cash
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Purchases
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
c. Accounts Payable-Schell Co.
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales
  • Sales Discounts
  • Sales Returns and Allowances
Inventory
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
d. Inventory
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales
Accounts Payable-Schell Co.
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales
  • Sales Discounts
  • Sales Returns and Allowances
e. Cash
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales
  • Sales Discounts
  • Sales Returns and Allowances
Accounts Payable-Schell Co.
  • Accounts Payable-Schell Co.
  • Cash
  • Cost of Merchandise Sold
  • Inventory
  • Sales Discounts
  • Sales Returns and Allowances
  • Sales

In: Accounting

This is for Cosmochemistry a) Assuming you wanted to study aqueously mediated chemistry and parent-body processing...

This is for Cosmochemistry

a) Assuming you wanted to study aqueously mediated chemistry and parent-body processing on an asteroid in the early solar system, name two materials you might study and why.

b) In comparison, if you were interested in understanding vapor-phase condensation in the early solar nebula, name two materials you might examine and why.

In: Chemistry

Using a correlation method, how can I explain scientific method steps to testing the validity of...

Using a correlation method, how can I explain scientific method steps to testing the validity of the folk wisdom idea saying "the early bird catches the worm". My theory is "You will have an advantage and be successful if you start early before anyone else does". i need at least 100 words. please help me.

In: Statistics and Probability

The Journal of Accounting Research (March 2008) published a study on relationship incentives and degree of...

The Journal of Accounting Research (March 2008) published a study on
relationship incentives and degree of optimism among analysts’ forecasts. Participants were
analysts at either a large or small brokerage firm who made their forecasts either early or late
in the quarter. Also, some analysts were only concerned with making an accurate forecast,
while others were also interested in their relationship with management. Suppose one of
these analysts is randomly selected. Consider the following events:
A = {The analyst is only concerned with making an accurate forecast},
B = {The analyst makes the forecast early in the quarter},
C = {The analyst is from a small brokerage firm}.
For each of the following, describe each of the events in terms of unions, intersections and
complements of events A, B and C.
a) The analyst makes an early forecast and is only concerned with accuracy.
(b) The analyst is not only concerned with accuracy.
(c) The analyst is from a small brokerage firm or makes an early forecast.
(d) The analyst makes a late forecast and is not only concerned with accuracy.

In: Statistics and Probability

In two complete paragraphs (5-8 sentences each), explain why doctors may not be comfortable labeling children...

In two complete paragraphs (5-8 sentences each), explain why doctors may not be comfortable labeling children as having a personality disorder? What are the negative implications of diagnosing children with personality disorders? What are the positive effects of early diagnosis?

Address the following topics within your response:

1. Medication-could this be a benefit or a drawback to the child. What about potential side effects? (5 points)
2. Labeling-could a young child just be going through a phase, how could a label such as schizophrenia negatively impact a child? (5 Points)
3. Educational/Career opportunities-Could early diagnosis gives an opportunity for more educational opportunities, and a better chance at having a fulfilling future
4. Family benefits-understanding that a child has a personality disorder and is not trying to be challenging may also impact the family dynamic as well. How could early diagnosis benefit the family or harm the family?
5. Society benefits-could early diagnosis prevent future crime when the child is an adult

In: Psychology

In two complete paragraphs (5-8 sentences each), explain why doctors may not be comfortable labeling children...

In two complete paragraphs (5-8 sentences each), explain why doctors may not be comfortable labeling children as having a personality disorder? What are the negative implications of diagnosing children with personality disorders? What are the positive effects of early diagnosis?

Address the following topics within your response:

1. Medication-could this be a benefit or a drawback to the child. What about potential side effects? (5 points)
2. Labeling-could a young child just be going through a phase, how could a label such as schizophrenia negatively impact a child? (5 Points)
3. Educational/Career opportunities-Could early diagnosis gives an opportunity for more educational opportunities, and a better chance at having a fulfilling future
4. Family benefits-understanding that a child has a personality disorder and is not trying to be challenging may also impact the family dynamic as well. How could early diagnosis benefit the family or harm the family?
5. Society benefits-could early diagnosis prevent future crime when the child is an adult

In: Psychology

In this question, we want to create a confidence interval for mu(m) - mu (u), the...

In this question, we want to create a confidence interval for mu(m) - mu (u), the difference in average Income between the genders: Male and Female. You may use the original data for this, or notice that I’ve included two rows in addition to the Exam1 data which has the incomes broken down by gender.

a) Check the conditions to construct a confidence interval for the difference in these two means.

b) Include the output from Minitab or Statcrunch showing the confidence interval of interest.

c) Interpret the interval in words relating to the original question.

Age (Years) Education (Years) Gender Student Married Ethnicity Income (Dollars/Year) Income of Females Income of Males
71 14 Female No Yes Asian 29705 29705 18145
56 15 Male No Yes African American 18145 55412 49502
37 16 Female Yes Yes Caucasian 55412 20974 140672
44 16 Female No Yes Caucasian 20974 30550 13647
81 9 Female No No African American 30550 75406 103893
55 14 Male No Yes Caucasian 49502 12000 10635
46 9 Male No Yes African American 140672 30007 15741
41 14 Female No Yes Asian 75406 152298 44205
47 14 Male No Yes Caucasian 13647 87625 42529
28 14 Female No Yes Caucasian 12000 30682 17316
69 9 Female No Yes Caucasian 30007 31335 32856
41 12 Female No Yes Asian 152298 19782 60449
84 17 Male No No Asian 103893 130209 149316
69 16 Male No Yes Asian 10635 27470 11603
46 10 Female No No African American 87625 28575 83869
39 14 Male No Yes Asian 15741 34509 24050
77 7 Female No No Caucasian 30682 58351 107841
38 7 Female No No Caucasian 31335 15079 33017
46 16 Female Yes No Caucasian 19782 30413 29567
39 19 Female No Yes Caucasian 130209 80616 26370
32 12 Male No Yes Caucasian 44205 57337 24824
32 11 Female No Yes Asian 27470 94193 30012
37 11 Male No Yes Asian 42529 69165 36364
65 13 Male No No African American 17316 27369 15717
60 11 Female No No African American 28575 58929 30111
80 18 Female No Yes African American 34509 59879 35691
68 13 Male No No Caucasian 32856 44473 91362
69 8 Male No Yes Caucasian 60449 37878 28144
80 16 Male No No African American 149316 16103 52179
85 16 Female No Yes Caucasian 58351 53401 25124
71 11 Male No Yes Caucasian 11603 10588 68713
28 15 Female No Yes Asian 15079 31811 62328
83 11 Male No No African American 83869 26067 69656
32 18 Male No Yes Caucasian 24050 19537 44522
87 7 Male No No African American 107841 36496 71682
28 16 Male No Yes African American 33017 24230 16304
25 15 Female Yes No Asian 30413 23350 23793
25 15 Male No No Caucasian 29567 26532 23672
57 7 Female No Yes Asian 80616 29403 27229
78 11 Male No Yes Asian 26370 148924 60579
45 7 Female No No Caucasian 57337 22939 13561
33 9 Male Yes No Caucasian 24824 22561 53480
33 17 Male No Yes Caucasian 30012 106025 55882
44 16 Female No Yes Caucasian 94193 65896 28508
34 11 Female No No African American 69165 80861 12414
40 9 Female No Yes Caucasian 27369 29638 23949
66 9 Female No Yes African American 58929 15846 23857
78 15 Female No No Caucasian 59879 15333 14887
81 16 Female No No African American 44473 32164 16479
50 19 Male No No Caucasian 36364 20936 33437
38 16 Male Yes Yes Caucasian 15717 55187 125480
80 13 Female No No Caucasian 37878 59855 24889
81 18 Male No Yes Caucasian 30111 21455 36362
45 10 Female No Yes Caucasian 16103 14084 67937
35 15 Male No No African American 35691 41419 83851
47 17 Male No Yes Asian 91362 27272 25974
35 12 Female No No African American 53401 63931 43682
66 13 Female No Yes Caucasian 10588 40885 20405
75 13 Female No Yes Caucasian 31811 19144 64173
74 17 Female No Yes African American 26067 20089 35610
51 10 Male No Yes Caucasian 28144 27847 85425
57 14 Male No No Asian 52179 18951 91876
34 9 Female No Yes Asian 19537 49927 41400
29 12 Male No Yes Caucasian 25124 13676 76348
56 16 Male Yes No Caucasian 68713 98515 23012
83 15 Male No No Caucasian 62328 10735 15354
41 14 Male No Yes African American 69656 27794 160231
72 15 Male No Yes Asian 44522 58165 121709
57 16 Male No Yes Caucasian 71682 36508 68462
69 15 Female No Yes Asian 36496 73914 113772
66 10 Male No Yes Asian 16304 41025 21153
70 14 Male No No African American 23793 36934 41532
63 11 Male No No Caucasian 23672 134181 31367
51 11 Male No No Caucasian 27229 76782
38 15 Male No Yes Asian 60579 30733
64 15 Female No Yes Caucasian 24230 53308
49 12 Female Yes No Caucasian 23350 55054
58 19 Female No Yes Caucasian 26532
37 19 Male No Yes Asian 13561
83 15 Male No No Caucasian 53480
68 16 Male No Yes Caucasian 55882
56 14 Male No Yes Asian 28508
37 14 Female No Yes Caucasian 29403
36 11 Female No No Asian 148924
32 12 Male No Yes African American 12414
47 18 Female No Yes Asian 22939
40 18 Male No Yes African American 23949
56 16 Male No Yes Caucasian 23857
58 12 Male No Yes African American 14887
66 15 Female No No Caucasian 22561
82 15 Female Yes Yes Asian 106025
49 17 Female No Yes Caucasian 65896
29 15 Female No Yes Asian 80861
26 16 Male No No African American 16479
29 15 Female No Yes Asian 29638
44 9 Male Yes No Caucasian 33437
53 12 Female No No Caucasian 15846
82 16 Male No Yes Caucasian 125480
75 12 Male No Yes Caucasian 24889
47 9 Female No Yes Asian 15333
79 15 Female No Yes African American 32164
30 15 Female No No Asian 20936
50 17 Female No Yes Caucasian 55187
49 15 Male No Yes African American 36362
63 12 Male No Yes Asian 67937
47 18 Male No No Caucasian 83851
46 13 Female No Yes Caucasian 59855
24 10 Male No No Asian 25974
49 9 Male No Yes Caucasian 43682
72 17 Male Yes No Asian 20405
80 12 Female No Yes African American 21455
46 17 Female No Yes African American 14084
80 10 Male No Yes Caucasian 64173
40 12 Male No No Caucasian 35610
60 12 Male No Yes African American 85425
24 11 Female Yes No Caucasian 41419
33 10 Male No Yes Caucasian 91876
67 10 Female No Yes Caucasian 27272
36 14 Male No Yes Caucasian 41400
60 18 Male No No Asian 76348
28 14 Female No Yes African American 63931
81 16 Male No No Caucasian 23012
46 13 Female No Yes African American 40885
65 14 Male No No Asian 15354
69 17 Male No No Caucasian 160231
75 13 Female No No African American 19144
57 15 Female No Yes African American 20089
50 6 Male No Yes Caucasian 121709
78 15 Female No Yes Caucasian 27847
71 16 Male No Yes Caucasian 68462
82 13 Female No No Caucasian 18951
75 17 Female No Yes Caucasian 49927
69 15 Male Yes Yes Caucasian 113772
41 11 Male No No Caucasian 21153
50 12 Male No Yes Caucasian 41532
30 10 Male No Yes Caucasian 31367
44 12 Male No Yes Asian 76782
51 13 Male No No Caucasian 30733
80 16 Female No No African American 13676
78 11 Female No No African American 98515
44 17 Female No Yes Caucasian 10735
35 8 Female No Yes African American 27794
84 10 Male No Yes Caucasian 53308
56 12 Female No Yes Caucasian 58165
74 17 Male No Yes Asian 55054
79 6 Female No Yes Caucasian 36508
67 15 Female No Yes Caucasian 73914
79 19 Female No Yes Caucasian 41025
63 9 Female No Yes Caucasian 36934
48 13 Female No No Caucasian 134181

In: Statistics and Probability

Sonic Inc. manufactures two models of speakers, Rumble and Thunder. Based on the following production and...

Sonic Inc. manufactures two models of speakers, Rumble and Thunder. Based on the following production and sales data for June, prepare (a) a sales budget and (b) a production budget: Rumble Thunder Estimated inventory (units), June 1 254 82 Desired inventory (units), June 30 292 71 Expected sales volume (units): Midwest Region 3,500 3,900 South Region 4,850 5,500 Unit sales price $135 $220 a. Prepare a sales budget. Sonic Inc. Sales Budget For the Month Ending June 30 Product and Area Unit Sales Volume Unit Selling Price Total Sales Model: Rumble Midwest Region $ $ South Region Total $ Model: Thunder Midwest Region $ $ South Region Total $ Total revenue from sales $ b. Prepare a production budget. For those boxes in which you must enter subtracted or negative numbers use a minus sign. Sonic Inc. Production Budget For the Month Ending June 30 Units Rumble Units Thunder Total units available Total units to be produced Check My Work

In: Accounting

Jackson Auto Parts Manufacturer, a U.S. based manufacturer of piston rings and other auto parts sold...

Jackson Auto Parts Manufacturer, a U.S. based manufacturer of piston rings and other auto parts sold parts to a South Korean Auto Manufacturer on December 1, 2020 with payment in 10 million South Korean Won to be received on March 31, 2021. The following exchange rates are relevant:

Date:    Spot Rate                Forward Rate

Dec 1, 2020 $0.0035 $0.0034

Dec 31, 2020 $0.0033 $0.0032

March 31 2021 $0.0038 $0.0032

Assuming Jackson did not hedge its foreign exchange risk, how much foreign exchange gain or loss should it report on its fiscal year end December 31, 2020 financial statements/

Assuming that Jackson did in fact decide to hedge its foreign exchange risk and entered into a forward exchange contract to sell 10 million South Korean Won on December 1, 2020 as a fair value hedge of a foreign currency receivable, what is the net impact on Jackson’s 2020 net income resulting from a fluctuation in the value of the Won? Ignore time value of money.

Defend your answer.

In: Accounting

Sales and Production Budgets Sonic Inc. manufactures two models of speakers, Rumble and Thunder. Based on...

Sales and Production Budgets

Sonic Inc. manufactures two models of speakers, Rumble and Thunder. Based on the following production and sales data for June, prepare (a) a sales budget and (b) a production budget:

Rumble Thunder
Estimated inventory (units), June 1 233 75
Desired inventory (units), June 30 268 65
Expected sales volume (units):
Midwest Region 2,600 2,900
South Region 5,050 5,700
Unit sales price $125 $195

a. Prepare a sales budget.

Sonic Inc.
Sales Budget
For the Month Ending June 30
Product and Area Unit Sales Volume Unit Selling Price Total Sales
Model: Rumble
Midwest Region
South Region
Total
Model: Thunder
Midwest Region
South Region
Total
Total revenue from sales

b. Prepare a production budget. For those boxes in which you must enter subtracted or negative numbers use a minus sign.

Sonic Inc.
Production Budget
For the Month Ending June 30
Units Rumble Units Thunder
Total units available
Total units to be produced

In: Accounting