Null Hypothesis: INF has a unit root Exogenous: Constant Bandwidth: 11 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Phillips-Perron test statistic Test critical values: 1% level 5% level 10% level *MacKinnon (1996) one-sided p-values. Residual variance (no correction) HAC corrected variance (Bartlett kernel) Phillips-Perron Test Equation Dependent Variable: D(INF) Method: Least Squares Date: 10/30/22 Time: 12:17 Sample (adjusted): 1992 2021 Included observations: 30 after adjustments Variable INF(-1) с R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Coefficient -0.162929 1.949024 Std. Error -1.976999 -3.670170 -2.963972 -2.621007 t-Statistic Prob.* 0.123463 Mean dependent var 0.092158 S.D. dependent var 1.437485 Akaike info criterion 57.85819 Schwarz criterion -52.42012 Hannan-Quinn criter. 0.2948 1.928606 0.909886 Prob. 0.082042 -1.985926 0.0569 1.111443 1.753598 0.0904 -0.195800 1.508684 3.628008 3.721421 3.657892

Null Hypothesis: INF has a unit root Exogenous: Constant Bandwidth: 11 (Newey-West automatic) using Bartlett kernel Adj. t-Stat Phillips-Perron test statistic Test critical values: 1% level 5% level 10% level MacKinnon (1996) one-sided p-values. Residual variance (no correction) HAC corrected variance (Bartlett kernel) Phillips-Perron Test Equation Dependent Variable: D(INF) Method: Least Squares Date: 10/30/22 Time: 12:17 Sample (adjusted): 1992 2021 Included observations: 30 after adjustments Variable INF(-1) с R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Coefficient -0.162929 1.949024 Std. Error -1.976999 -3.670170 -2.963972 -2.621007 t-Statistic Prob. 0.123463 Mean dependent var 0.092158 S.D. dependent var 1.437485 Akaike info criterion 57.85819 Schwarz criterion -52.42012 Hannan-Quinn criter. 0.2948 1.928606 0.909886 Prob. 0.082042 -1.985926 0.0569 1.111443 1.753598 0.0904 -0.195800 1.508684 3.628008 3.721421 3.657892

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 5E: Population Genetics In the study of population genetics, an important measure of inbreeding is the...

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Population Genetics In the study of population genetics, an important measure of inbreeding is the proportion of homozygous genotypesthat is, instances in which the two alleles carried at a particular site on an individuals chromosomes are both the same. For population in which blood-related individual mate, them is a higher than expected frequency of homozygous individuals. Examples of such populations include endangered or rare species, selectively bred breeds, and isolated populations. in general. the frequency of homozygous children from mating of blood-related parents is greater than that for children from unrelated parents Measured over a large number of generations, the proportion of heterozygous genotypesthat is, nonhomozygous genotypeschanges by a constant factor 1 from generation to generation. The factor 1 is a number between 0 and 1. If 1=0.75, for example then the proportion of heterozygous individuals in the population decreases by 25 in each generation In this case, after 10 generations, the proportion of heterozygous individuals in the population decreases by 94.37, since 0.7510=0.0563, or 5.63. In other words, 94.37 of the population is homozygous. For specific types of matings, the proportion of heterozygous genotypes can be related to that of previous generations and is found from an equation. For mating between siblings 1 can be determined as the largest value of for which 2=12+14. This equation comes from carefully accounting for the genotypes for the present generation the 2 term in terms of those previous two generations represented by for the parents generation and by the constant term of the grandparents generation. a Find both solutions to the quadratic equation above and identify which is 1 use a horizontal span of 1 to 1 in this exercise and the following exercise. b After 5 generations, what proportion of the population will be homozygous? c After 20 generations, what proportion of the population will be homozygous?
State whether the following statements are true, false or uncertain and provide a very brief justification. No marks will be awarded for just saying true, false or uncertain.a) In general, an instrumental variables estimator is less accurate than the OLS estimator.b) The assumption of homoscedasticity states that the variance of the OLS residuals is constant.c) Weighted least squares is used to control for inconsistency in our estimators.d) Many econometricians contend that the use of instruments can help one obtain better estimators in certain cases.
The breaking strengths of cables produced by a certain company are approximately normally distributed. The company announced that the mean breaking strength is 2150 pounds with a variance of 36,100. A consumer protection agency claims that the actual variance is higher. Suppose that the consumer agency wants to carry out a hypothesis test to see if its claim can be supported. State the null hypothesis H0 and the alternative hypothesis H1they would use for this test. H0: H1:
a:- Show that the significant value of t at level of significance h for one-tailed test is equal to that of t at 2h significance level for two-tailed test. b:- It is a common experience that the volatility ( measured in terms of variance) of a financial market strategy is less than 0.25. Define the null and alternative hypothesis for testyyour faith oj this strategy.Perform a test at 1% level of significance to check the precision of a good undergoing this strategy.Following are the prices (in ruppes) of a particular good:. 2.9, 3.1, 3.2, 2.8, 2.7, 3.4, 2.6, 3.0, 3.3, 2.9, 2.8, 3.5
Which statement is false? Levine's test for the quality of variance is used with the dependent t-test The dependent t-test is considered more powerful than the independent t-test Parametric tests are considered more powerful than non-parametric You can typically use a small sample with the dependent t-test compared to the independent t-test
3. In the 1980s, Tennessee conducted an experiment in which kindergarten students were randomly assigned to "regular" and "small" classes, and given standardized tests at the end of the year. (Regular classes contained approximately 24 students, and small classes contained approximately 15 students.) Suppose, in the population, the standardized tests have a mean score of 925 points and a standard deviation of 75 points. Let SmallClass denote a binary variable equal to 1 if the student is assigned to a small class and equal to 0 otherwise. A regression of TestScore on SmallClass yields = TestScore = 918.0 + 13.9 × SmallClass, R2 = 0.01, SER = 74.6 (1.6) (2.5)(a) Do small classes improve test scores? By how much? Is the effect large? Explain.(b) Is the estimated effect of class size on test scores statistically significant? Carry out a test at the 5% level.(c) Construct a 99% confidence interval for the effect of SmallClass on TestScore. (d) Does least squares assumption 1 plausibly hold…
Test the claim that the proportion of people who own cats is larger than 20% at the 0.05 significance level.The null and alternative hypothesis would be: H0:p≤0.2H1:p>0.2 H0:p≥0.2H1:p<0.2 H0:μ≥0.2H1:μ<0.2 H0:μ=0.2H1:μ≠0.2 H0:μ≤0.2H1:μ>0.2 H0:p=0.2H1:p≠0.2 The test is: left-tailed two-tailed right-tailed Based on a sample of 400 people, 28% owned catsThe test statistic is: (to 2 decimals)The p-value is: (to 2 decimals)Based on this we: Fail to reject the null hypothesis Reject the null hypothesis
Exercise A: In building an arena, steel bars with a mean ultimate tensile strength of 400 Megapascal (MPa) with a variance of 81 MPa were delivered by the manufacturer. The project engineer tested 50 steel bars and found out that the mean ultimate tensile strength is 390 MPa. The decision for the extension of the contract with the manufacturer depends on the engineer. Test the hypothesis whether or not there is no significant difference between the two means using a two-tailed test with α = 0.01. What are the appropriate hypotheses for the two-tailed test? What is the test statistic to be used and the reasons for its selection? What is the critical value c? What is the value of the test statistic or the computed value? Formulate a conclusion about the given situation.
Independent-samples t test: (a) develop a research question that can be addressed with independent-samples t test, (b) state the null and alternative hypotheses (in words), (c) state the alpha level, (d) run the analysis, and (e) provide interpretation of results (including checks for assumptions and effect size) following APA format.
1. A manufacturer of chocolate chips would like to know whether its bag filling machine works correctly at the 426 gram setting. It is believed that the machine is underfilling the bags. A 99 bag sample had a mean of 417 grams with a variance of 400. A level of significance of 0.10.1 will be used. Assume the population distribution is approximately normal. Determine the decision rule for rejecting the null hypothesis. Round your answer to three decimal places. Reject H0 if t < blank ? 2.Using traditional methods, it takes 9.4 hours to receive a basic driving license. A new license training method using Computer Aided Instruction (CAI) has been proposed. A researcher used the technique with 24 students and observed that they had a mean of 9.6 hours with a standard deviation of 1.4. A level of significance of 0.1 will be used to determine if the technique performs differently than the traditional method. Assume the population distribution is approximately normal. Find the value of the…
Lerven's test of equality of variances shows: 1. The result is significant, so the variances are not different 2. The result is significant, so the variances are different 3. The result is non-significant, so the variances are not different 4. The result is non-significant, so the variances are different From the Levene’s test result, what might you conclude about the use of the t test? 1. The assumption of equal variances is met, so the use of the t test may be appropriate 2. The assumption of equal variances is not met, so the use of the t test may be inappropriate 3. The assumption of equal variances is not met, so the use of the t test may be appropriate 4. The assumption of equal variances is met, so the use of the t test may be inappropriate