+1 678 648 4277 

Authentic Gretl assignment help to boost your grades

Are your Gretl assignments becoming too difficult for you to handle? Consider taking professional help with Gretl assignment. GNU Regression, Econometrics, & Time-series Library (Gretl) is a statistical program used for performing statistical analysis. It requires deep knowledge of the concepts in order to complete the assignments effectively. Thanks to our reputed Gretl assignment help platform, students can have these homework completed in a manner that secures them good grades without having to memorize intricate concepts.

GET FREE QUOTE
  1. Homepage
  2. Gretl assignment help
Table Of Contents
  • Hypothesis test conducted by our Gretl homework help experts

Hypothesis test conducted by our Gretl homework help experts

status
  Frequency Percent  
  Employed 59 25.5  
Retired 172 74.5  
Total 231 100.0  
25.5% are employed and 74.5 are retired, the proportion of employed is 0.255 and the proportion of retired is 0.745. Our Gretl homework help experts give the sampling error as: For pemployed

At a 5% level of significance,the z tab is 1.96. Therefore, Z calc (7.45)>Ztab(1.96). In our Gretl homework solution, we reject the null hypothesis and conclude that the proportion is significantly different

Measures of central tendency covered by our Gretl experts

  Fitness social enjoy medical
frequency percent frequency percent frequency percent Frequency percent
1 5 2.2 49 21.2 10 4.3 17 7.4
2 2 0.9 35 15.2 9 3 26 11.3
3 4 1.7 60 26 47 20.3 25 10.8
4 26 11.3 48 20.8 67 29 62 26.8
5 194 84 38 16.5 98 42.4 100 43.3
rank   Top Box Top Box 2 mean ` median std.dev sampling error
1 fitness 5(84%) 4(11.3) 4.74 5 0.735 0.094785
2 enjoy 5(42.4%) 4(29%) 4.01 4 1.085 0.13992
3 medical 5(43.3%) 4(26.8%) 3.9 4 1.311 0.169065
4 Social 3(26%*) 1(21.2%) 2.97 3 1.383 0.17835  
The upper part of the table above presents the frequency distribution, for fitness, we observe that 84% see participation as very important for fitness, 16.5% very important for social 42.4% see it very important for enjoyment and 43.3% see it very important for medical.
  1. The lower part of the table in 2 presents the top two box, the top two boxes for fitness is response 5 which constitutes 84% and response 4 (11.3%). For social the top two boxes are 3 (26%) and 1(21.2%).moreover, for enjoying the top box is 5(42.4%) and 4 (29%). Similarly for medical, the top box is 5(43%) and 4 (26%)
  2. the lower part of table 2 also presents the mean, median, and standard deviation for the variables. For fitness the average is 4.74, the deviation from the mean is 0.735 while the median is 5. For social, the average is 2.97, the deviation from the mean is 1.383 while the median is 3. For enjoyment, the average is 4.01, the deviation from the mean is 1.085 while the median is 4 and finally for medical, the average is 3.9, the deviation from the mean is 1.311 while the median is 4.
Our Gretl experts calculate the sampling error as:

5


pair mean difference std.err t Df p
fitness- social 1.766 1.419 18.913 230 0.000
fitness- enjoy 0.727 1.138 9.614 230 0.000
fitness-medical 0.844 1.329 9.652 230 0.000
social-enjoy -1.309 1.458 -10.834 230 0.000
social-medical -0.922 1.738 -8.064 230 0.000
enjoy-medical 0.117 1.618 1.098 230 0.273
6 The result of the test of difference in means is presentedin the table above. According to our online Gretl tutors there exits significant difference between fitness and social (t(230)=18.913,p=0.000<0.05), fitness and enjoy (t(230)=9.614,p=0.000<0.05), fitness and medical (t(230)=9.652,p=0.000<0.05), social and enjoy (t(230)=-10.834,p=0.000<0.05), social and medical (t(230)=-8.064,p=0.000<0.05). However, there is no significant difference in mean of (t(230)=1.098,p=0.273>0.05). 7
  mean difference std.err t df p
Visits 1.519 0.505 3.009 230 0.003
The result presented above shows that the average number of monthly visits is significantly different from the national average of 8 (t(230)=1.519,p=0.003). The mean difference is 1.519
  doctor recommend  
NO YES Total
utilized pool therapy NO Count 107 20 127
% within pool 84.30% 15.70% 100.00%
% within doctor 60.50% 37.00% 55.00%
YES Count 70 34 104
% within pool 67.30% 32.70% 100.00%
% within doctor 39.50% 63.00% 45.00%
Total Count 177 54 231
% within pool 76.60% 23.40% 100.00%
% within doctor 100.00% 100.00% 100.00%
value df P
Pearson ci-square 9.165 1 0.02
Phi 0.19   0.02    
  1. 45% utilize therapy pool while 55%do does not utilize therapy pool
  2. 67.30% of those who used the therapy pool is not recommended by a doctor
  3. 63% of those recommended by a doctor utilized the therapy pool
  4. thePearson chi-square shows that there exists a significant association between the pool and doctor recommendation as chi2(1)=9.165 and p=0.02<0.05
  5. The phi-value tests the strength of the association between variables. The phi value is 0.19 which is a weak association. Therefore, the association between utilizing therapy pool and government recommendation is weak
13
  mean std error t df p
employed 7.53 0.854
retired 10.2 0.604
difference -2.678 1.147 -2.335 229 0.02
The table above shows that the mean of retired (M=10.2) is greater than the mean visits of employed (7.53). The difference is statistically significant at 5% level (t(229)=2.335, p=0.02) 14
  fitness social enjoy medical
Fitness 1 0.230** 0.229** 0.217**
Social 0.230** 1 0.323** 0.196**
Enjoy 0.229** 0.323** 1 0.138*
Medical 0.217** 0.196** 0.138* 1
correlation is significant at 0.01 level (2-tailed)
correlation is significant at 0.05 level (2-tailed)
The spearman rank correlation coefficient is presented above, significant correlation is starred. The result shows that a significant correlation exists between all the variables. However, all the correlations are weak except the correlation between social and enjoy which is a medium (r=0.323)

Analysis of variance

  fitness social enjoy medical
fitness 4.74 (0.74) 0.230** 0.229** 0.217**
social 0.230** 2.97(1.38) 0.323** 0.196**
enjoy 0.229** 0.323** 4.01(1.08) 0.138*
medical 0.217** 0.196** 0.138* 3.90(1.31)
standard deviations in parenthesis
**Correlation is significant at 0.01 level (2-tailed)
*Correlation is significant at 0.05 level (2-tailed) 16
ANOVA  
Model Sum of Squares df Mean Square F Sig.  
Regression 538827.3 5 107765.5 4.156 .001  
Residual 5834695 225 25931.98      
Total 6373522 230        
The table above is the result of the test of significance of the while model. The model is statistically significant as F(5,225)=4.156, p=0.001<0.05 17
Model R R Square Adjusted R Square Std. The error of the Estimate
  0.291 0.085 0.064 161.0341
The coefficient of determination (R2) is 0.085 and 0.064 after adjustment. This implies that the independent variables in the model account for only 6.4% of the variation in the dependent variable.

Sample tests conducted by our Gretl assignment helpers

Coefficients estimates Std. Error t Sig.
(Constant) 165.529 81.689 2.026 0.044
fitness 12.66 16.575 0.764 0.446
social 30.617 8.308 3.685 0.000
enjoy -28.059 10.685 -2.626 0.009
medical 3.958 8.496 0.466 0.642
recom 6.699 8.106 0.826 0.409
Our Gretl assignment helpers determine the significance of the coefficient by comparing their respective p-value with the level of significance. If the p-value less than the significance level, the variable is significant otherwise, the variable is not significant. Looking at the result, fitness is not statistically significant p=0.46>0.05 as well as medical, p=0.42>0.05, the same goes to recom, p=0.409>0.05. however, social is statistically significant as p=0.000<0.05. Moreover, those that view social as the importance of attending AFC adds to revenue $30.62 more than others. In the same vein, enjoyment is also statistically significant as p=0.009<0.05. Respondents that view enjoyments as the importance of attending AFC on average a $30.62 less than others. 19 According to our Gretl assignment help experts, changing the level of significance to 0.01 does not affect the significance of the result 20 The recommendations are as follows:
  1. The management should target the retired people as they visit more often than the employed people
  2. Management should liaise more with doctors as 65% of those recommended by doctors utilize the therapy pool. This is to increase revenue.
  3. Those who view social as important for attending AFC have a revenue premium over others. Therefore, revenue can be increased by targeting more of people who have this view.
  4. Those who view enjoyment as important for attending AFC have a revenue deficit over others. Therefore, revenue can be increased by targeting less of people who have this view

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 538827.294 5 107765.459 4.156 .001b
Residual 5834695.137 225 25931.978    
Total 6373522.431 230      
a. Dependent Variable: revenue
b. Predictors: (Constant), recom, medical, social, enjoy, fitness