ECONOMETRICS & BUSINESS STATISTICS

Econometrics & Business Statistics



Econometrics & Business Statistics

Randomly select 100 numbers from the attached table with replacement (that is, you may select the same number more than once), and then compute the sample mean and the sample standard deviation of preferred values.

Sample

704

587

459

523

467

549

661

465

446

406

566

713

378

696

608

299

374

474

779

365

452

433

469

526

167

613

355

547

359

779

532

562

642

377

211

364

547

643

488

312

762

208

698

731

391

547

547

343

610

567

556

640

442

704

361

377

394

403

532

424

555

380

831

435

574

274

593

404

644

195

729

294

265

960

294

706

577

483

609

257

999

328

756

390

521

340

251

888

730

608

455

647

212

856

744

667

481

712

403

855

Descriptive Statistics

N

Range

Minimum

Maximum

Sum

Mean

Std. Deviation

Variance

Skewness

Kurtosis

Statistic

Statistic

Statistic

Statistic

Statistic

Statistic

Std. Error

Statistic

Statistic

Statistic

Std. Error

Statistic

Std. Error

Sample of 100

100

832

167

999

52036

520.36

18.010

180.095

3.243E4

.288

.241

-.342

.478

Valid N (list wise)

100

The result of the descriptive chart is showing the mean of the sample size that is 100 that is 520.36 and standard deviation is 180.095. Descriptive statistics is a big part of the statistic that is dedicated to analyze and represent data. This analysis is very basic. Although there is a tendency to generalize the entire population, the first conclusions reached after a descriptive analysis is a study by calculating a series of measures of central tendency, to see to what extent the data is grouped or scattered around a central value, this is what could be an approximate concept. The purpose of the descriptive statistics is to process, the empirical data and their systematization, a visual representation in the form of graphs and tables, as well as their quantitative description of the means of key statistical indicators.

In contrast to inductive statistics, descriptive statistics does not make conclusions about the population based on the results of the study of particular cases. Inductive same statistics on the contrary suggests that the properties and laws identified in the study sample sites, also inherent in the population.

Find a 95 % confidence interval for the population-mean preferred value. State clearly what assumption(s) you made and/or what theorem(s) you used in answering this question.

In the context of a population parameter estimate, a confidence interval is a range of values ??(calculated in a sample) in which lies the true value of the parameter with a given probability. The probability that the true parameter value is in the interval constructed is called the confidence level, denoted 1 - a. The likelihood of mistakes is called level of significance and symbolizes. Usually built with confidence intervals 1 - a = 95 % (or significance = 5 %). Less frequent are the intervals = 10 % o = 10 % or = 1 %. = 1 %.To construct a confidence interval can be checked that meets Standard Normal Distribution:

P (- 1.96 < z < 1.96) = 0.95

(This can be checked with a probability table or a computer program to calculate normal probabilities).

Then, if a variable X has distribution N ( , s2), Then 95 % of the time is fulfilled:

Solving in the equation we have:

The result is a range that includes the 95 % of the time. That is, a confidence interval for the average 95 % normal y when the variable X is normal s2and is known.

485.0614

µ

555.6586

The company asks you if their belief that the population-mean preferred value is greater than $510,000 is correct. Perform a hypothesis test to see if there is strong evidence for this.

The single sample t test was used to test whether the mean of a ...