Consider the following model of the Philips curve. In this model inflation is regressedupon unemployment using a sample of 56 observations, where INF denotes ameasure of the inflation rate and UNEM denotes a measure of the unemployment rate.An initial analysis of this model produced the results reported in Tables Two and Three.Table TwoDependent Variable: INFMethod: Least SquaresSample: 1948 2003Included observations: 56Coeficient Sid. Emor -Statistic Prob.VariableUNEM1.053565 1.547957 0.680617 0.49900.502378 0.265562 1.891752 00639Schwarz criterion 5.123418Akaike info criterion 5051084Table ThreeBreusch-Godtrey Serial Correlation LM TestFatatisticObs'R-squared31.52897 Prob. F(1,53)20.88778 Prob. Chi-Square(1)0.00000.0000Further analysis produced the results in Tables Four and Five.Table FourDependent Variable: INFMethod: Least SquaresSample (aqusted) 1950 2003Included observations: 54 afer adjustmentsVariableCoefficient Sid. Emor-StatistieProb.INF(-1)UNEMUNEM-1)UNEM-2)1.40901108331230.42144102037121.139049 1.2368200.104146 7.9005340.314574 1.3397220.3500920.22200.00000.18650.57310.05650.5672960.50403802580681.953120Akake info criterion 4.178055Schwarz oriterion 4362220Table FiveBreusch-Godtey Serial Correlation LM TestFatatstieObs"R-aquared2325230 Prob. F(1,48)2495029 Prob. Ch-Square(1)0.13300.1142c) Compare the two models presented in Tables Two and Four on the basis of the calculatedvalues of the information criteria considered. Using appropriate justification, explain whichmodel you prefer.d) A new ARDL (2,3) model of INF is estimated, with no serial autocorrelation detectedfor this model. The calculated values of the Schwarz Information Criterion and AkaikeInformation criterion for this model are given as:The Schwarz Information Criterion = 4.443694The Akaike Information Criterion = 4.183467Compare this model with those presented in Tables Two and Four. Which of the threemodels do you prefer? Explain your answer.

c) The model with lowest value of AIC (Akaike info criterion) and lowest schwarz criterion is…

Answered: Consider the following model of the…

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
Which non-parametrical test for ordinal data is the best use in the given scenario? In a study by Grape et. al, researchers investigated the possible beneficial effects of singing on well-being during a single singing lesson. One of the variables of interest was the change in cortisol as a result of the singing lesson. Use the data in the following table to determine if, in general, cortisol increases after a singing lesson. Let a = 0.05. Find the p value. Subject 1 2 3 4 5 6 7 8 Before 214 362 202 158 403 219 307 331 After 232 276 224 412 562 203 340 313 a. Kruskal-Wallis Test b. Sign Test c. Spearman and Kendall Correlation Coefficients d. Wilcoxon Rank Sum Test e. Mood Median Test f. Wilcoxon Matched-Pairs Signed-Ranks Test
Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: Intercept educ IQ KWW exper black feduc meduc Least Squares Wed, 23 Nov 2022 08:57:40 coef -503.0058 40.5455 3.1654 7.2094 16.2338 -59.2987 10.8278 5.0471 std err nonrobust 138.947 8.660 1.199 wage OLS 2.120 3.740 52.143 5.353 6.106 722 714 7 R-squared: Adj. R-squared: Prob (F-statistic): F-statistic: Log-Likelihood: AIC: BIC: -3.620 4.682 2.640 3.400 4.340 -1.137 2.023 0.827 P> [t] 0.000 -775.800 0.000 0.008 0.001 0.000 0.256 0.043 0.409 0.189 0.181 23.83 23.543 0.812 3.047 8.891 -161.671 0.318 -6.941 3.310-29 -5288.5 (0.025 0.9751 1.0590+04 1.063e+04 -230.212 57.548 5.519 11.372 23.577 43.074 21.338 17.035 Above is a regression of men's monthly earnings in dollars as a function of their years of education, their IQ score in "points", their Knowledge of the World of Work (KWW) score in points (a measure of their knowledge of how occupations work), their years of work experience…
Hi there! Is there anyone on here confident on SPSS that would be able to help?
Which non-parametric test for ordinal data is the best to use in the given scenario? In a study by Zuckerman and Heneghan, hemodynamic stresses were measured on subjects undergoing laparoscopic cholecystectomy. An outcome variable of interest was the ventricular end-diastolic volume (LVEDV) measured in mm. A portion of the data appears in the following table. Baseline refers to a measurement taken 5 minutes after induction of anesthesia, and the term '5 minutes' refers to a measurement taken 5 minutes after baseline. Can we conclude that, on the basis of these data, among subjects undergoing laparoscopic cholecystectomy, the average LVEDV levels change? Let a =.01. LVEDV (ml) Subject Baseline 5 minutes 1 51.7 49.3 2 79.0 72.0 3 78.7 67.0 4 80.3 70.4 5 72.0 65.9 6 85.0 84.8 7 79.0 77.7 8 71.3 74.0 9 54.3 58.0 10 58.8 65.0 a. Mood Median Test b. Sign Test c. Wilcoxon Rank Sum Test d. Wilcoxon Matched-Pair Signed-Ranks Test e. Spearman and Kendall Correlation…
Would someone familiar with SPSS be able to help with sub-question d please?
A Logistic Regression model was used for classifying common brushtail possums into their two regions. The outcome variable takes value 1 if the possum was from Victoria and 0 otherwise. We consider five predictors: sex_male (an indicator for a possum being male), head length, skull width, total length, and tail length. A summary table is provided below. Estimate Std. Error Z value Pr(>||I) (Intercept) 33.5095 9.9053 3.38 0.0007 sex_male -1.4207 0.6457 -2.20 0.0278 0.0231 skull_width total_length tail_length -0.2787 0.1226 -2.27 0.5687 0.1322 4.30 0.0000 -1.8057 0.3599 -5.02 0.0000 Suppose we see a brushtail possum at a zoo in the US, and a sign says the possum had been captured in the wild in Australia, but it doesn't say which part of Australia. However, the sign does indicate that the possum is female, its skull is about 53 mm wide, its total length is 93 cm and its tail is 40 cm long. What is the predicted probability that this possum is from Victoria? Choose an option that is…
B. What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is____°F. C. What is wrong with this predicted value? The first variable should have been the dependent variable. It is unrealistically high. The value 3000 is far outside of the range of observed values. It is only an approximation. An unrounded value would be considered accurate. Nothing is wrong with this value. It can be treated as an accurate prediction.
B. What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is____°F. C. What is wrong with this predicted value? The first variable should have been the dependent variable. It is unrealistically high. The value 3000 is far outside of the range of observed values. It is only an approximation. An unrounded value would be considered accurate. Nothing is wrong with this value. It can be treated as an accurate prediction.

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