## Lesson 13: Careers in Real Estate

Review:

- Ben Vonderwahl
- Manufactured homes
- Owner financing

Presentation:

- Guest Speaker
- Kelly Conner Young, The Platinum Group

Category: Teaching

- 17 hours ago
- f17-econ491
- Justin

Review:

- Ben Vonderwahl
- Manufactured homes
- Owner financing

Presentation:

- Guest Speaker
- Kelly Conner Young, The Platinum Group

- 2 days ago
- f17-busad265
- Justin

Review:

- Sampling Distributions

Presentation:

**How to Estimate a Population Mean (μ)**- Conduct a Simple Random Sample (SRS) of size
*n* - Calculate the sample mean, x
*-bar = (∑x)/n* - If
*n*is sufficiently large (≥30), we can assume*x-bar*is Normally distributed - Estimate of the population mean,
*μ = x-bar*(point estimate) - Estimate of the population standard deviation,
*σ = s/(√n)* - Estimate margin of error,
*m = z*σ*(use*z*= 1.96 for 95% confidence) - Estimate with confidence interval for
*μ =**x-bar ± m*

- Conduct a Simple Random Sample (SRS) of size
- Watch video
- Example: A sample of size n = 400 produced the sample mean, x-bar = 36.0 and sample standard deviation, s = 9.0. Construct a 95% confidence interval to estimate the population mean.
- n = 400
- x-bar = 36.0
- s = 9.0
- m = 1.96*(9/(√400)) = 0.882
- Estimate for μ = 36.0 ± 0.882
- 95% confidence interval: [35.118, 36.882]

Assignment:

**Problem 1**. A sample of size n = 100 produced the sample mean, x-bar = 16.0 and sample standard deviation, s = 3.0. Construct a 95% confidence interval to estimate the population mean.**Problem 2**. An operation manager at a large plant observed 120 workers assembling an electronic component. The average time needed for assembly was 16.2 minutes with a standard deviation of 3.6 minutes. Construct a 95% confidence interval to estimate the mean assembly time.**Problem 3**. A computer technician installs new hard drives on 64 different computers. The average installation time is 42 minutes with a standard deviation of 5 minutes. Construct a 95% confidence interval for the mean installation time.**Problem 4**. A research firm conducted a survey of regular smokers to estimate the average amount spent per week on cigarettes. A sample of 49 regular smokers revealed average spending on cigarettes to be $21.55 with a standard deviation of $5.21. Construct a 95% confidence interval to estimate mean weekly cigarette spending.

Study:

- Read pp. 353-362, Introduction to Inference and Estimating with Confidence

- 3 days ago
- f17-econ491
- Justin

Review:

- Exam 2 Results

Presentation:

- Guest Speaker: Ben Vonderwahl

- 4 days ago
- f17-busad265
- Justin

Review:

- Exam 2 Results

Presentation:

- Sampling Distributions
- Take multiple Simple Random Samples, sample size = n, and calculate sample mean
- “Sampling Distribution” is the distribution of sample means
- Standard deviation of sample means =
**σ/√n** - Example 5.18 on p. 338

- Central Limit Theorem
- Simple random samples of size n from
**any**population with mean μ and finite standard distribution σ. When n is large (typically ≥ 30), the sampling distribution of the sample mean is approximately**Normal**. - Example 5.19 on p. 339

- Simple random samples of size n from
- Video

Assignment:

- Complete Exercises 5.36, 5.37, 5.38, 5.39 on pp. 336-340
- Read pp. 335-344, Sampling Distribution of a Sample Mean

- 4 days ago
- f17-busad265
- Justin

Exam2 | |

Mean | 85.1 |

Standard Error | 1.5 |

Median | 86.9 |

Mode | 97.2 |

Standard Deviation | 11.9 |

Sample Variance | 140.9 |

Kurtosis | 2.7 |

Skewness | -1.3 |

Range | 60.6 |

Minimum | 39.4 |

Maximum | 100.0 |

Sum | 5361.2 |

Count | 63.0 |

- 1 week ago
- f17-econ491
- Justin

Exam 2 on Thu, Oct 12

- Open notes
- No phones, laptops, watches
- No talking or collaborating with neighbors
- No leaving classroom
- Term Papers Due
**Nov 2** - Scheduling Presentations for Nov 7, 9, 14, 16
- Days/time slots are first come, first serve

- Jeremy Grantham with Charlie Rose

Topics:

- 2008 Housing/Mortgage/Financial Crisis
- Monetary Policy
- Federal Reserve
- Alan Greenspan
- Ben Bernanke
- Tim Geitner

- Securitization and Derivatives
- Mortgage backed securities (MBS)
- Collateralized Debt Obligations (CDOs)
- Credit Default Swaps

- Subprime Lending
- Low-income borrowers
- Predatory lending
- Loan origination fees/bonuses

- Deregulation
- Laissez-faire capitalism, Reaganomics
- 1999 Gramm-Leach-Bliley Act – repeals 1933 Glass-Steagall Act
- 2000 Commodity Futures Modernization Act – prevents regulation of most derivatives
- 2004 SEC proposes “voluntary regulation” and lower capital requirements

- Mortgage Meltdown
- Skyrocketing default rates
- Dropping property values
- Strategic default
- Neighborhood deterioration

- Crisis Culprits
- Banks’ Excessive Leverage
- Subprime Lenders
- Federal Reserve Low Interest Rates
- Rating Agencies
- Secondary Mortgage Market
- Fannie Mae
- Freddie Mac

- Greedy Borrowers (the only group punished)

- 2 weeks ago
- f17-busad265
- Justin

Exam 2 on Wed, Oct 11

- Open book, notes, calculator
- No phones, laptops, watches
- No talking with neighbors
- No leaving classroom

Topics:

- Scatterplots
- Linear Regression
- Sum of Squares
- Regression line calculations
- Pearson Correlation Coefficient
- R-Squared

- Design of Experiments
- Explanatory variables
- Response variables
- Subjects
- Treatments
- Placebo effect
- Bias
- Double-blind

- Sampling
- Census vs Sampling
- Sampling Types
- Voluntary response
- Simple random sample (SRS)
- Stratified random sample

- Two-way tables
- Marginal distribution
- Joint distribution
- Conditional distribution

- Causation
- vs Correlation
- Lurking variables
- Retrospective studies
- Prospective studies

- Probability
- Random phenomenon
- Short term outcomes uncertain
- Long term outcomes predictable
- Independent trials
- Discrete vs Continuous
- Probability Rules
- Discrete probability distribution table calculations

- 2 weeks ago
- f17-econ491
- Justin

Review:

- Derivatives
- Term Assignment Preview
- Presentation or Paper
- Team or Solo
- 1-page outline

**Exam 2 next week on Thu, Oct 12**- Guest speakers Oct 17 & 19

Presentation:

- Fannie Mae and Freddie Mac
- Fannie Mae = Federal National Mortgage Association (FNMA)
- Freddie Mac = Federal Home Loan Mortgage Corporation (FHLMC)
- Government Sponsored Enterprises (GSEs)
- Fannie chartered by congress in 1968
- Freddie chartered by congress in 1970
- President of the US appoints 5 of 18 member board of directors
- Treasury is authorized to purchase securities from Fannie and Freddie
- Regulated by Dept of Housing and Urban Development (HUD) and Federal Housing Finance Agency (FHFA)
- Implicit guarantee of federal bailout

- Secondary Market for mortgage loans
- Provide liquidity to loan originators
- Gives lenders flexibility
- Monopoly for Fannie and Freddie issuing securities
- Monopoly ended when Wall Street joined the party ~2000
- When Fannie/Freddie market share decreased (after 2000), they began purchasing and guaranteeing
**subprime**loans

- Government Rescue: Conservatorship
- Losses piled up in 2007
- FHFA placed Fannie and Freddie under govt control on Sep 6, 2008

- Federal Housing Administration (FHA)
- Increasingly competitive between FHA + Fannie/Freddie

- Mortgage Crisis – Key Culprits
- Wall Street Banks selling MBS and CDO securities
- Losers: Bear Stearns, Lehman Brothers, Merrill Lynch
- Winners: Goldman Sachs, Citigroup, JP Morgan, others

- Subprime Loan Originators pushing ARMs and other non-traditional loans on low-income borrowers
- New Century Financial
- Countrywide Financial

- Federal Reserve
- Keeping interest rates too low for too long
- Failing to regulate mortgage market and derivatives

- Rating Agencies issuing AAA ratings on low quality MBS and CDOs
- Moody’s
- Standard and Poor’s

- Professional Investors/Hedge Funds
- Increasing volatility through use of excessive leverage

- Fannie and Freddie
- Purchasing subprime loans in the secondary market
- Providing liquidity for ongoing subprime lending

- Wall Street Banks selling MBS and CDO securities

Assignment:

- Study for Exam 2
- Work on term project

- 2 weeks ago
- f17-busad265
- Justin

Review:

- Probability
**Exam 2 on Wed, Oct 11**

Presentation:

- Random Variables
- Discrete Random Variables
- Probability distribution table

- Continuous Random Variables
- Area under a density curve

- video

- Discrete Random Variables

- Example Problem
- The random variable x, defined below, gives the average grade of 12th grade students in U.S. high schools. The probability distribution for x is given in Table 20.11.

x = {4 if A average, 3 if B average, 2 if C average, 1 if D average}a. Find P x( 3) ≥ , the probability that a randomly selected student has a B or better average.

b. Find P x( 3) < , the probability that a randomly selected student has a below B average. How is this probability related to your answer to (a)?

c. Make a probability histogram for the distribution of x. What does your graphic display tell you about the distribution of average grades?

- The random variable x, defined below, gives the average grade of 12th grade students in U.S. high schools. The probability distribution for x is given in Table 20.11.

Assignment:

**Problem 1.** The U.S. government collects data on many variables having to do with households.

Let x = the number of children under 15 in a household. The probability distribution for x is shown in the table below.

a. What is the probability that a randomly selected household has at least one child under 15?

b. What is the probability that a randomly selected household has between two and four children under 15? In other words, find P (2 ≤ x ≤ 4).

c. Draw a probability histogram that represents the probability distribution shown in the table above.

**Problem 2.** Assume that the distribution of weight for 7½-week old hens is normally distributed with mean 544 grams and standard deviation 49 grams. Let w = weight of a randomly selected hen.

a. Sketch normal density curve representing the distribution of w.

Use technology or the standard normal table to find the probabilities in (b) – (d). On a copy of the normal density curve that you sketched for (a), shade the area under the curve that represents each probability.

b. P ( w < 500)

c. P (w ≥ 580)

d. P (500 ≤ w ≤ 580)

*Problems 1 and 2 are from AgainstAllOdds_StudentGuide_Unit20 duplicated here for convenience.*

- 2 weeks ago
- f17-econ491
- Justin

Review:

- Recovery
- Fiscal Policy
**Exam 2 on Thu, Oct 12**

Presentation:

- Group Discussion
- Same groups from last week
- Understanding Derivatives
- Snippets from the Big Short
- Proposals for derivatives
- Ban
- Regulate
- Tax
- Laissez-faire

Assignment:

- Work on term project