On 4/6/2000, Airbnb, the home-sharing company, said it was raising $1 billion from private-equity firms Silver Lake and Sixth Street Partners to bolster its financing. The funding comes at a steep price: $1 billion of debt with an interest rate of more than 10%. While some investors declined to put in new money after Airbnb said it wouldn't replace its CEO and others didn't participate because they didn't think the terms were favorable, Silver Lake and Sixth Street Partners said they had faith in the business and existing leadership team. Airbnb hasn't addressed its plans for a public offering, which had previously been considered the hottest prospective IPO of 2020. Airbnb is now weighing plans to raise as much as $1 billion more in new financing, said the people familiar with the matter.
According to the WSJ article (please see the attached under Week2 reading assignment), please discuss (1) The issues facing Airbnb stemming from Covid-19. (2) Irrespective of Covid-19, what challenges does Airbnb face with respect to its cost structure and business model? (3) Why are the financing terms for the $1 billion it raised so onerous? What other financing options do you believe Airbnb could have explored?
In: Economics
Farmer Inc. began business on January 1, 2019. Its pretax financial income for the first 2 years was as follows:
2019 $340,000
2020 760,000
The following items caused the only differences between pretax financial income and taxable income.
1. In 2019, the company collected $420,000 of rent; of this amount, $140,000 was earned in 2019; the other $280,000 will be earned equally over the 2020–2021 periods. The full $420,000 was included in taxable income in 2019.
2. The company pays $20,000 a year for life insurance on officers.
3. In 2020, the company terminated a top executive and agreed to $90,000 of severance pay. The amount will be paid $30,000 per year for 2020–2022. The 2020 payment was made. The $90,000 was expensed in 2020 for financial reporting purposes. For tax purposes, the severance pay is deductible as it is paid.
4. The company purchased a large asset in 2019 for $60,000. The depreciation will be computed using a five-year life. For tax purposes, the company will be able to deduct half of the cost in 2019 and in 2020.
The enacted tax rates existing on December 31, 2019, are:
2019 30% 2021 40%
2020 35% 2022 40%
Instructions:
(a) Determine taxable income for 2019 and 2020.
(b) Determine the deferred income taxes at the end of 2019, and prepare the journal entry to record income taxes for 2019.
(c) Prepare a schedule of future taxable and (deductible) amounts at the end of 2020.
(d) Prepare a schedule of the deferred tax (asset) and liability at the end of 2020.
(e) Compute the net deferred tax expense (benefit) for 2020.
(f) Prepare the journal entry to record income taxes for 2020.
In: Accounting
which of the following is not related to genetic drift?
neutral variation
sexual selection
non darwinian evolution
bottleneck effect
founder effect
In: Biology
P14–19Ethics Problem Assume that you are the CFO of a company contemplating a stock repurchase next quarter. You know that there are several methods of reducing the current quarterly earnings, which may cause the stock price to fall prior to the announcement of the proposed stock repurchase. What course of action would you recommend to your CEO? If your CEO came to you first and recommended reducing the current quarter’s earnings, what would be your response?
In: Accounting
The following information is available for Ivanhoe Company. 1. Purchased a copyright on January 1, 2020 for $62,400. It is estimated to have a 10-year life. 2. On July 1, 2020, legal fees for successful defense of the copyright purchased on January 1, 2020, were $17,784.
Prepare the journal entries to record all the events related to
the copyright during 2020. (Credit account titles are
automatically indented when the amount is entered. Do not indent
manually.)
Jan 1st 2020, July 1st, 2020, Dec 31st, 2020
At December 31, 2021, an impairment test is performed on the
copyright purchased in 2020.
It is estimated that the net cash flows to be received from the
copyright will be $62,400, and its fair value is $59,280. The
accumulated amortization at the end of 2021 was $15,288. Compute
the amount of impairment, if any, to be recorded on December 31,
2021. (If there is a loss on impairment, then enter
amounts using either a negative sign preceding the number e.g. -45
or parentheses e.g. (45).)
| Amount of impairment | $ |
In: Accounting
You have heard from idle chatter that most students don't declare a major in their MBA programs. You took a sample of 200 students (in the data file). Conduct a one-sample hypothesis test to determine if the proportion without a major is greater than 50%. Use a .05 significance level.
| ID | Gender | Major | Employ | Age | MBA_GPA |
| 1 | 0 | No Major | Unemployed | 39 | 2.82 |
| 2 | 1 | No Major | Full Time | 55 | 4 |
| 3 | 0 | No Major | Part Time | 43 | 3.45 |
| 4 | 0 | No Major | Full Time | 56 | 2.61 |
| 5 | 1 | No Major | Full Time | 38 | 3.5 |
| 6 | 0 | No Major | Unemployed | 54 | 4 |
| 7 | 0 | No Major | Full Time | 30 | 3 |
| 8 | 0 | No Major | Full Time | 37 | 2.5 |
| 9 | 0 | No Major | Part Time | 38 | 2.84 |
| 10 | 0 | No Major | Full Time | 42 | 3.72 |
| 11 | 0 | No Major | Part Time | 52 | 3.21 |
| 12 | 0 | No Major | Full Time | 35 | 3.44 |
| 13 | 0 | No Major | Full Time | 37 | 3.65 |
| 14 | 0 | No Major | Full Time | 53 | 3.02 |
| 15 | 0 | No Major | Part Time | 51 | 3.03 |
| 16 | 1 | No Major | Full Time | 40 | 3.8 |
| 17 | 0 | Finance | Full Time | 33 | 4 |
| 18 | 0 | No Major | Part Time | 53 | 3.26 |
| 19 | 0 | No Major | Full Time | 43 | 3.53 |
| 20 | 0 | Finance | Unemployed | 35 | 3.75 |
| 21 | 0 | No Major | Full Time | 57 | 3.15 |
| 22 | 1 | No Major | Part Time | 32 | 3.66 |
| 23 | 1 | No Major | Full Time | 59 | 3.36 |
| 24 | 1 | No Major | Full Time | 48 | 3.79 |
| 25 | 1 | No Major | Part Time | 34 | 2.85 |
| 26 | 1 | No Major | Full Time | 53 | 3.74 |
| 27 | 1 | No Major | Part Time | 35 | 3.23 |
| 28 | 1 | No Major | Unemployed | 38 | 3.52 |
| 29 | 1 | No Major | Part Time | 37 | 3.32 |
| 30 | 0 | Finance | Full Time | 46 | 2.89 |
| 31 | 0 | No Major | Full Time | 44 | 2.83 |
| 32 | 0 | No Major | Unemployed | 31 | 2.93 |
| 33 | 0 | No Major | Full Time | 51 | 3.71 |
| 34 | 0 | Finance | Full Time | 47 | 3.47 |
| 35 | 0 | No Major | Part Time | 56 | 3.52 |
| 36 | 1 | Finance | Part Time | 42 | 2.83 |
| 37 | 0 | Finance | Full Time | 44 | 3.64 |
| 38 | 0 | No Major | Unemployed | 54 | 2.96 |
| 39 | 0 | Finance | Full Time | 51 | 3.59 |
| 40 | 0 | No Major | Part Time | 42 | 3.33 |
| 41 | 0 | Finance | Full Time | 45 | 3.38 |
| 42 | 0 | Finance | Full Time | 55 | 3.44 |
| 43 | 0 | No Major | Full Time | 47 | 3.31 |
| 44 | 1 | Finance | Unemployed | 43 | 3.03 |
| 45 | 0 | Finance | Full Time | 57 | 3.26 |
| 46 | 1 | Finance | Full Time | 36 | 3.04 |
| 47 | 1 | No Major | Part Time | 58 | 2.98 |
| 48 | 1 | Finance | Full Time | 46 | 2.8 |
| 49 | 1 | Finance | Full Time | 53 | 3.75 |
| 50 | 0 | Finance | Full Time | 59 | 3.64 |
| 51 | 0 | No Major | Full Time | 49 | 3.65 |
| 52 | 0 | Finance | Full Time | 34 | 3.18 |
| 53 | 0 | No Major | Full Time | 46 | 3.44 |
| 54 | 1 | Finance | Unemployed | 46 | 3.06 |
| 55 | 1 | Finance | Full Time | 33 | 3.51 |
| 56 | 1 | Marketing | Part Time | 56 | 3.33 |
| 57 | 1 | Marketing | Full Time | 39 | 2.81 |
| 58 | 1 | Marketing | Full Time | 51 | 3.64 |
| 59 | 1 | Leadership | Part Time | 55 | 3.05 |
| 60 | 1 | Leadership | Full Time | 38 | 2.85 |
| 61 | 1 | Marketing | Full Time | 33 | 3.56 |
| 62 | 1 | Marketing | Full Time | 34 | 2.92 |
| 63 | 1 | Marketing | Full Time | 31 | 3.35 |
| 64 | 1 | Marketing | Full Time | 37 | 3.46 |
| 65 | 1 | Marketing | Full Time | 46 | 3.59 |
| 66 | 1 | No Major | Unemployed | 31 | 3.11 |
| 67 | 1 | No Major | Full Time | 47 | 3.65 |
| 68 | 1 | No Major | Part Time | 54 | 3.17 |
| 69 | 1 | No Major | Full Time | 52 | 2.97 |
| 70 | 1 | Marketing | Part Time | 43 | 3.77 |
| 71 | 1 | Leadership | Full Time | 44 | 3.21 |
| 72 | 1 | Leadership | Part Time | 34 | 3.17 |
| 73 | 1 | Leadership | Full Time | 59 | 3.65 |
| 74 | 1 | Leadership | Full Time | 45 | 2.94 |
| 75 | 1 | Leadership | Full Time | 30 | 3.53 |
| 76 | 1 | No Major | Full Time | 32 | 3.65 |
| 77 | 1 | Leadership | Full Time | 32 | 3.61 |
| 78 | 1 | No Major | Full Time | 40 | 3.7 |
| 79 | 1 | Leadership | Full Time | 48 | 2.91 |
| 80 | 1 | Leadership | Unemployed | 51 | 3.09 |
| 81 | 1 | Leadership | Full Time | 30 | 3.77 |
| 82 | 1 | Leadership | Full Time | 31 | 3.79 |
| 83 | 1 | Leadership | Full Time | 35 | 3.59 |
| 84 | 1 | Leadership | Full Time | 33 | 3.38 |
| 85 | 1 | No Major | Full Time | 35 | 4 |
| 86 | 1 | Marketing | Full Time | 31 | 2.97 |
| 87 | 1 | Marketing | Full Time | 38 | 3.44 |
| 88 | 1 | No Major | Part Time | 46 | 3.64 |
| 89 | 1 | Finance | Full Time | 45 | 3.48 |
| 90 | 1 | Finance | Full Time | 59 | 2.76 |
| 91 | 1 | Finance | Full Time | 58 | 3.73 |
| 92 | 1 | Finance | Full Time | 46 | 2.91 |
| 93 | 1 | Finance | Full Time | 35 | 3.78 |
| 94 | 1 | Finance | Part Time | 53 | 3.5 |
| 95 | 1 | Finance | Full Time | 31 | 3.13 |
| 96 | 1 | Finance | Full Time | 50 | 3.14 |
| 97 | 1 | Finance | Full Time | 38 | 3.24 |
| 98 | 1 | Finance | Full Time | 50 | 3.56 |
| 99 | 1 | Finance | Full Time | 48 | 3.16 |
| 100 | 1 | Finance | Full Time | 53 | 3.53 |
| 101 | 0 | No Major | Unemployed | 53 | 3.7 |
| 102 | 0 | Marketing | Full Time | 30 | 3.3 |
| 103 | 0 | Marketing | Part Time | 32 | 4 |
| 104 | 0 | Leadership | Full Time | 42 | 3.5 |
| 105 | 0 | Leadership | Full Time | 56 | 3.39 |
| 106 | 0 | No Major | Full Time | 46 | 3.65 |
| 107 | 0 | Leadership | Full Time | 49 | 2.78 |
| 108 | 0 | No Major | Part Time | 32 | 3.44 |
| 109 | 0 | No Major | Full Time | 36 | 3.88 |
| 110 | 0 | No Major | Full Time | 42 | 2.84 |
| 111 | 0 | No Major | Part Time | 37 | 3.53 |
| 112 | 0 | No Major | Full Time | 31 | 3.22 |
| 113 | 0 | No Major | Full Time | 31 | 3.56 |
| 114 | 0 | No Major | Unemployed | 42 | 3.2 |
| 115 | 0 | No Major | Full Time | 39 | 3.56 |
| 116 | 0 | No Major | Full Time | 47 | 3.41 |
| 117 | 0 | Leadership | Part Time | 28 | 3.56 |
| 118 | 0 | Leadership | Unemployed | 28 | 3.34 |
| 119 | 0 | Leadership | Full Time | 52 | 2.56 |
| 120 | 0 | Leadership | Part Time | 35 | 3.76 |
| 121 | 1 | Finance | Full Time | 38 | 3.55 |
| 122 | 1 | No Major | Full Time | 44 | 3.88 |
| 123 | 1 | No Major | Part Time | 38 | 3.31 |
| 124 | 1 | Finance | Full Time | 52 | 3.09 |
| 125 | 1 | Finance | Unemployed | 53 | 3.82 |
| 126 | 1 | Finance | Part Time | 53 | 3.01 |
| 127 | 1 | Finance | Full Time | 31 | 3.66 |
| 128 | 1 | Finance | Part Time | 47 | 3.64 |
| 129 | 1 | Finance | Full Time | 51 | 3.59 |
| 130 | 1 | Finance | Unemployed | 37 | 3.49 |
| 131 | 1 | Finance | Part Time | 46 | 3.13 |
| 132 | 1 | Finance | Full Time | 48 | 3.83 |
| 133 | 1 | Leadership | Full Time | 54 | 3.04 |
| 134 | 1 | Leadership | Full Time | 48 | 3.91 |
| 135 | 1 | Leadership | Full Time | 36 | 3.56 |
| 136 | 1 | Finance | Unemployed | 39 | 3.96 |
| 137 | 1 | Finance | Full Time | 28 | 3.46 |
| 138 | 1 | Finance | Part Time | 45 | 3.22 |
| 139 | 1 | Finance | Full Time | 31 | 3.27 |
| 140 | 1 | Finance | Full Time | 47 | 3.43 |
| 141 | 1 | Finance | Part Time | 35 | 3.85 |
| 142 | 1 | Finance | Full Time | 52 | 3.89 |
| 143 | 0 | Finance | Part Time | 52 | 3.37 |
| 144 | 1 | Finance | Unemployed | 55 | 3.32 |
| 145 | 1 | Finance | Full Time | 52 | 3.54 |
| 146 | 1 | Finance | Part Time | 46 | 3.8 |
| 147 | 1 | Leadership | Full Time | 31 | 3.74 |
| 148 | 1 | Leadership | Unemployed | 33 | 3.6 |
| 149 | 1 | Leadership | Part Time | 45 | 2.6 |
| 150 | 1 | Leadership | Unemployed | 50 | 3.8 |
| 151 | 1 | No Major | Part Time | 33 | 2.67 |
| 152 | 1 | No Major | Full Time | 37 | 3.95 |
| 153 | 1 | No Major | Unemployed | 33 | 3.56 |
| 154 | 1 | Marketing | Full Time | 46 | 3.79 |
| 155 | 1 | Marketing | Unemployed | 55 | 3.93 |
| 156 | 1 | Marketing | Full Time | 30 | 3.79 |
| 157 | 1 | Marketing | Full Time | 51 | 3.71 |
| 158 | 1 | Marketing | Unemployed | 35 | 3.05 |
| 159 | 1 | Marketing | Unemployed | 40 | 3.22 |
| 160 | 0 | Marketing | Part Time | 29 | 3.85 |
| 161 | 1 | Marketing | Full Time | 52 | 3.82 |
| 162 | 1 | Marketing | Unemployed | 27 | 3.23 |
| 163 | 1 | Marketing | Full Time | 51 | 3.56 |
| 164 | 0 | Marketing | Part Time | 56 | 3.53 |
| 165 | 1 | Marketing | Unemployed | 35 | 3.62 |
| 166 | 1 | Leadership | Full Time | 46 | 3.8 |
| 167 | 1 | Leadership | Part Time | 39 | 3.47 |
| 168 | 1 | Leadership | Full Time | 31 | 3.64 |
| 169 | 1 | Leadership | Part Time | 52 | 3.03 |
| 170 | 1 | Leadership | Unemployed | 35 | 3.17 |
| 171 | 1 | Leadership | Full Time | 32 | 3.22 |
| 172 | 0 | Leadership | Part Time | 44 | 3.92 |
| 173 | 1 | Leadership | Unemployed | 43 | 3.82 |
| 174 | 1 | Leadership | Part Time | 38 | 3.26 |
| 175 | 1 | Leadership | Full Time | 54 | 3.8 |
| 176 | 1 | Leadership | Full Time | 30 | 3.2 |
| 177 | 0 | Leadership | Part Time | 38 | 3.46 |
| 178 | 1 | Leadership | Full Time | 45 | 3.67 |
| 179 | 1 | Leadership | Unemployed | 48 | 4 |
| 180 | 1 | Leadership | Full Time | 43 | 3.66 |
| 181 | 0 | Leadership | Full Time | 34 | 3.96 |
| 182 | 1 | Leadership | Full Time | 54 | 3.75 |
| 183 | 1 | Leadership | Full Time | 36 | 3.83 |
| 184 | 1 | Leadership | Full Time | 45 | 3.55 |
| 185 | 0 | Leadership | Unemployed | 55 | 3.36 |
| 186 | 1 | Leadership | Part Time | 45 | 3.21 |
| 187 | 1 | Leadership | Part Time | 34 | 2.97 |
| 188 | 0 | Leadership | Part Time | 54 | 3.99 |
| 189 | 1 | Leadership | Full Time | 36 | 3.07 |
| 190 | 1 | Leadership | Full Time | 24 | 3.65 |
| 191 | 1 | Leadership | Full Time | 34 | 3.67 |
| 192 | 1 | Leadership | Full Time | 45 | 3.06 |
| 193 | 1 | Leadership | Unemployed | 33 | 3.98 |
| 194 | 1 | Leadership | Full Time | 22 | 3.93 |
| 195 | 1 | Leadership | Unemployed | 27 | 3.41 |
| 196 | 1 | Leadership | Unemployed | 33 | 3.43 |
| 197 | 1 | Leadership | Unemployed | 36 | 3.7 |
| 198 | 1 | Leadership | Unemployed | 34 | 3.76 |
| 199 | 1 | Leadership | Unemployed | 55 | 3.9 |
| 200 | 1 | Leadership | Full Time | 33 | 3.23 |
In: Statistics and Probability
2)Business Weekly conducted a survey of graduates from 30 top
MBA programs. On the basis of the survey, assume the mean annual
salary for graduates 10 years after graduation is 132000 dollars.
Assume the standard deviation is 31000 dollars. Suppose you take a
simple random sample of 59 graduates.
Find the probability that a single randomly selected salary has a
mean value between 116260.2 and 145318.3 dollars.
P(116260.2 < X < 145318.3)
= (Enter your answers as numbers accurate to 4 decimal
places.)
Find the probability that a random sample of size n=59n=59 has a
mean value between 116260.2 and 145318.3 dollars.
P(116260.2 < ¯xx¯ < 145318.3) = (Enter
your answers as numbers accurate to 4 decimal places.)
3)A leading magazine (like Barron's) reported at one time that
the average number of weeks an individual is unemployed is 36.1
weeks. Assume that for the population of all unemployed individuals
the population mean length of unemployment is 36.1 weeks and that
the population standard deviation is 5.4 weeks. Suppose you would
like to select a random sample of 91 unemployed individuals for a
follow-up study.
Find the probability that a single randomly selected value is
between 35 and 37.2.
P(35 < X < 37.2) =
Find the probability that a sample of size n=91n=91 is randomly
selected with a mean between 35 and 37.2.
P(35 < ¯xx¯ < 37.2) =
Enter your answers as numbers accurate to 4 decimal places.
4)CNNBC recently reported that the mean annual cost of auto
insurance is 957 dollars. Assume the standard deviation is 271
dollars. You take a simple random sample of 73 auto insurance
policies. (Do not use tables unless directed to do so.)
Find the probability that a single randomly selected value is more
than 994 dollars.
P(X > 994) =
Find the probability that a sample of size n=73n=73 is randomly
selected with a mean that is more than 994 dollars.
P(¯xx¯ > 994) =
Enter your answers as numbers accurate to 4 decimal places.
5)Business Weekly conducted a survey of graduates from 30 top
MBA programs. On the basis of the survey, assume the mean annual
salary for graduates 10 years after graduation is 168000 dollars.
Assume the standard deviation is 43000 dollars. Suppose you take a
simple random sample of 70 graduates.
Do not use probability tables to find the probabilities below as
they may not be accurate enough.
Find the probability that a single randomly selected salary is more
than 164000 dollars.
P(X > 164000) =
Find the probability that a sample of size n=70n=70 is randomly
selected with a mean that is more than 164000 dollars.
P(¯xx¯ > 164000) =
Enter your answers as numbers accurate to 4 decimal places.
6)A leading magazine (like Barron's) reported at one time that
the average number of weeks an individual is unemployed is 23
weeks. Assume that for the population of all unemployed individuals
the population mean length of unemployment is 23 weeks and that the
population standard deviation is 9 weeks. Suppose you would like to
select a random sample of 38 unemployed individuals for a follow-up
study.
Find the probability that a single randomly selected value is less
than 24.
P(X < 24) =
Find the probability that a sample of size n=38n=38 is randomly
selected with a mean less than 24.
P(¯xx¯ < 24) =
Enter your answers as numbers accurate to 4 decimal places.
7)A company produces steel rods. The lengths of the steel rods
are normally distributed with a mean of 261.5-cm and a standard
deviation of 0.5-cm. For shipment, 13 steel rods are bundled
together.
Find the probability that the average length of a randomly selected
bundle of steel rods is less than 261.7-cm.
P(¯xx¯ < 261.7-cm) =
Enter your answer as a number accurate to 4 decimal places.
In: Statistics and Probability
2)Business Weekly conducted a survey of graduates from 30 top
MBA programs. On the basis of the survey, assume the mean annual
salary for graduates 10 years after graduation is 132000 dollars.
Assume the standard deviation is 31000 dollars. Suppose you take a
simple random sample of 59 graduates.
Find the probability that a single randomly selected salary has a
mean value between 116260.2 and 145318.3 dollars.
P(116260.2 < X < 145318.3)
= (Enter your answers as numbers accurate to 4 decimal
places.)
Find the probability that a random sample of size n=59n=59 has a
mean value between 116260.2 and 145318.3 dollars.
P(116260.2 < ¯xx¯ < 145318.3) = (Enter
your answers as numbers accurate to 4 decimal places.)
3)A leading magazine (like Barron's) reported at one time that
the average number of weeks an individual is unemployed is 36.1
weeks. Assume that for the population of all unemployed individuals
the population mean length of unemployment is 36.1 weeks and that
the population standard deviation is 5.4 weeks. Suppose you would
like to select a random sample of 91 unemployed individuals for a
follow-up study.
Find the probability that a single randomly selected value is
between 35 and 37.2.
P(35 < X < 37.2) =
Find the probability that a sample of size n=91n=91 is randomly
selected with a mean between 35 and 37.2.
P(35 < ¯xx¯ < 37.2) =
Enter your answers as numbers accurate to 4 decimal places.
4)CNNBC recently reported that the mean annual cost of auto
insurance is 957 dollars. Assume the standard deviation is 271
dollars. You take a simple random sample of 73 auto insurance
policies. (Do not use tables unless directed to do so.)
Find the probability that a single randomly selected value is more
than 994 dollars.
P(X > 994) =
Find the probability that a sample of size n=73n=73 is randomly
selected with a mean that is more than 994 dollars.
P(¯xx¯ > 994) =
Enter your answers as numbers accurate to 4 decimal places.
5)Business Weekly conducted a survey of graduates from 30 top
MBA programs. On the basis of the survey, assume the mean annual
salary for graduates 10 years after graduation is 168000 dollars.
Assume the standard deviation is 43000 dollars. Suppose you take a
simple random sample of 70 graduates.
Do not use probability tables to find the probabilities below as
they may not be accurate enough.
Find the probability that a single randomly selected salary is more
than 164000 dollars.
P(X > 164000) =
Find the probability that a sample of size n=70n=70 is randomly
selected with a mean that is more than 164000 dollars.
P(¯xx¯ > 164000) =
Enter your answers as numbers accurate to 4 decimal places.
6)A leading magazine (like Barron's) reported at one time that
the average number of weeks an individual is unemployed is 23
weeks. Assume that for the population of all unemployed individuals
the population mean length of unemployment is 23 weeks and that the
population standard deviation is 9 weeks. Suppose you would like to
select a random sample of 38 unemployed individuals for a follow-up
study.
Find the probability that a single randomly selected value is less
than 24.
P(X < 24) =
Find the probability that a sample of size n=38n=38 is randomly
selected with a mean less than 24.
P(¯xx¯ < 24) =
Enter your answers as numbers accurate to 4 decimal places.
7)A company produces steel rods. The lengths of the steel rods
are normally distributed with a mean of 261.5-cm and a standard
deviation of 0.5-cm. For shipment, 13 steel rods are bundled
together.
Find the probability that the average length of a randomly selected
bundle of steel rods is less than 261.7-cm.
P(¯xx¯ < 261.7-cm) =
Enter your answer as a number accurate to 4 decimal places.
In: Statistics and Probability
You are a Software QA Professional and are now interviewing at Google for your next job. While in the interview, the QA Manager taking your interview asks you the following question: “Let’s say you log a bug that you find while executing 1 of your test cases. But the developer replies back and says that this is not a valid bug. How would you tackle this situation and what would be your next steps?” Provide a thorough and complete answer to this interview question.
In: Computer Science
HRMT
1. Refer to an organization and job position you are familiar with. Describe a selection test you would use as part of your hiring process and your rationale for using the test. Describe the critical points you would consider in selecting the test.
2- What sources of information create interview impressions that influence the interview process and outcomes? Provide an example of an interview impression error you have experienced and how you would reduce the effects of this inaccurate impression in future interviews.
In: Operations Management