The company has the following account balances on June 1, 2020. (all accounts have their ‘normal’ balances)
Drawings: 1000
Cash: 20000
Service revenue: 50000
Capital: 15000
Depreciation Expense: 700
Equipment: 30000
Accounts Payable: 5000
Insurance Expense: 500
Unearned Service Revenue: 4000
Prepaid Service Revenue: 500
Accounts Receivable: 4000
Rent Expense: 5000
Salaries Expense: 16000
Accumulated Depreciation - Equipment: 3000
During June 2018, the following events took place. Where appropriate, record a journal entry for each transaction. If no journal entry is required, write ‘no entry’.
|
Date |
Account name & description |
Debit |
Credit |
Explanation is needed if the item needs to to be calculated.
In: Accounting
The company has the following account balances on June 1, 2020. (all accounts have their ‘normal’ balances)
Drawings: 1000
Cash: 20000
Service revenue: 50000
Capital: 15000
Depreciation Expense: 700
Equipment: 30000
Accounts Payable: 5000
Insurance Expense: 500
Unearned Service Revenue: 4000
Prepaid Service Revenue: 500
Accounts Receivable: 4000
Rent Expense: 5000
Salaries Expense: 16000
Accumulated Depreciation - Equipment: 3000
During June 2018, the following events took place. Where appropriate, record a journal entry for each transaction. If no journal entry is required, write ‘no entry’.
Question: Open T-accounts using the beginning balances provided and post entries into T-accounts. Calculate the balance of each one.
In: Accounting
1. In December 2005, the BLS estimated there were 7.4 million unemployed, 142.8 million employed (including 2.8 million involuntary part-time workers), 451,000 discouraged workers and 4.8 million people (including discouraged workers) who were marginally attached to the labor force.
a. Calculate the headline (U-3) unemployment rate for December 2005.
b. Calculate the unemployment rate for December 2005 if it had included among the unemployed all officially discouraged workers.
c. Calculate the unemployment rate if it had included all those who were marginally attached to the labor force?
d. Calculate the unemployment rate if it had included all those who were marginally attached to the labor force plus involuntary part-time workers.
In: Economics
This is the trial balance of Cullumber Company on September 30.
| CULLUMBER COMPANY Trial Balance September 30, 2022 |
||||
|---|---|---|---|---|
|
Debit |
Credit |
|||
|
Cash |
$ 24,020 | |||
|
Accounts Receivable |
7,420 | |||
|
Supplies |
4,210 | |||
|
Equipment |
10,110 | |||
|
Accounts Payable |
$ 9,620 | |||
|
Unearned Service Revenue |
3,210 | |||
|
Common Stock |
19,820 | |||
|
Retained Earnings |
13,110 | |||
| $45,760 | $45,760 | |||
The October transactions were as follows.
| Oct. 5 | Received $1,380 in cash from customers for accounts receivable due. | |
| 10 | Billed customers for services performed $5,870. | |
| 15 | Paid employee salaries $1,030. | |
| 17 | Performed $550 of services in exchange for cash. | |
| 20 | Paid $1,980 to creditors for accounts payable due. | |
| 29 | Paid a $320 cash dividend. | |
| 31 |
Paid utilities $380 |
Post to the ledger accounts. (Post entries in the order of information presented in the question.)
In: Accounting
Part1. Calculate the nuclear binding energy (in J) and the nuclear binding energy per nucleon of
| 241 | Pu | |
| 94 |
(241.0568453 amu).
Part 2.
A freshly isolated sample of 90Y was found to have an activity of 8.2 × 105 disintegrations per minute at 1:00 p.m. on December 3, 2006. At 2:15 p.m. on December 17, 2006, its activity was measured again and found to be 2.2 × 104 disintegrations per minute. Calculate the half-life of 90Y.
In: Chemistry
In: Economics
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In: Accounting
| 26. | It is best to require foreign customers that are relatively unknown to you pay in one | ||||||||
| of the two following methods: | |||||||||
| 1 | |||||||||
| 2 | |||||||||
| 27. | Provide 2 problems when credit terms are too strict: | ||||||||
| 1 | |||||||||
| 2 | |||||||||
In: Finance
An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead). Consumers, of all income and wealth classes, were surveyed. Every year, 1500 consumers were interviewed. The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually. Below is the data shown for the last 24 years.
Date X Y (in thousands of dollars)
1994 79.1 55.6
1995 79 54.8
1996 80.2 55.4
1997 80.5 55.9
1998 81.2 56.4
1999 80.8 57.3
2000 81.2 57
2001 80.7 57.5
2002 80.3 56.9
2003 79.4 55.8
2004 78.6 56.1
2005 78.3 55.7
2006 78.3 55.7
2007 77.8 55
2008 77.7 54.4
2009 77.6 54
2010 77.6 56
2011 78.5 56.7
2012 78.3 56.3
2013 78.5 57.2
2014 78.9 57.8
2015 79.8 58.7
2016 80.4 59.3
2017 80.7 59.9
Questions:
In: Statistics and Probability
Is the number of tornadoes increasing? In the last homework, data on the number of tornadoes in the United States between 1953 and 2014 were analyzed to see if there was a linear trend over time. Some argue that it’s not the number of tornadoes increasing over time, but rather the probability of sighting them because there are more people living in the United States. Let’s investigate this by including the U.S. census count (in thousands) as an additional explanatory variable (data in EX11-24TWISTER.csv).
Perform a multiple regression using both year and census count as explanatory variables. Write down the fitted model. Are year and census count respectively significant in the MLR model?
|
Year |
Tornadoes |
Census |
|
1953 |
421 |
158956 |
|
1954 |
550 |
161884 |
|
1955 |
593 |
165069 |
|
1956 |
504 |
168088 |
|
1957 |
856 |
171187 |
|
1958 |
564 |
174149 |
|
1959 |
604 |
177135 |
|
1960 |
616 |
179979 |
|
1961 |
697 |
182992 |
|
1962 |
657 |
185771 |
|
1963 |
464 |
188483 |
|
1964 |
704 |
191141 |
|
1965 |
906 |
193526 |
|
1966 |
585 |
195576 |
|
1967 |
926 |
197457 |
|
1968 |
660 |
199399 |
|
1969 |
608 |
201385 |
|
1970 |
653 |
203984 |
|
1971 |
888 |
206827 |
|
1972 |
741 |
209284 |
|
1973 |
1102 |
211357 |
|
1974 |
947 |
213342 |
|
1975 |
920 |
215465 |
|
1976 |
835 |
217563 |
|
1977 |
852 |
219760 |
|
1978 |
788 |
222095 |
|
1979 |
852 |
224567 |
|
1980 |
866 |
227225 |
|
1981 |
783 |
229466 |
|
1982 |
1046 |
231664 |
|
1983 |
931 |
233792 |
|
1984 |
907 |
235825 |
|
1985 |
684 |
237924 |
|
1986 |
764 |
240133 |
|
1987 |
656 |
242289 |
|
1988 |
702 |
244499 |
|
1989 |
856 |
246819 |
|
1990 |
1133 |
249623 |
|
1991 |
1132 |
252981 |
|
1992 |
1298 |
256514 |
|
1993 |
1176 |
259919 |
|
1994 |
1082 |
263126 |
|
1995 |
1235 |
266278 |
|
1996 |
1173 |
269394 |
|
1997 |
1148 |
272647 |
|
1998 |
1449 |
275854 |
|
1999 |
1340 |
279040 |
|
2000 |
1075 |
282224 |
|
2001 |
1215 |
285318 |
|
2002 |
934 |
288369 |
|
2003 |
1374 |
290447 |
|
2004 |
1817 |
293191 |
|
2005 |
1265 |
295895 |
|
2006 |
1103 |
298754 |
|
2007 |
1096 |
301621 |
|
2008 |
1692 |
304059 |
|
2009 |
1156 |
308746 |
|
2010 |
1282 |
309347 |
|
2011 |
1691 |
311722 |
|
2012 |
938 |
314112 |
|
2013 |
907 |
316498 |
|
2014 |
888 |
318857 |
In: Statistics and Probability