Question

patient no	age	market encounter	incubation period	hospitalization period	total infection time	time in ICU	ventilator required	status after hospitalization
1	49	worker	5,74763199	10,4375707	16,1852026	5,69262998	yes	recovered
2	95	customer	7,69709556	12,4477736	20,1448692	0	no	X
3	84	customer	4,43152382	15,9523951	20,3839189	3,12372819	yes	X
4	62	customer	14,5976098	8,27617448	22,8737843	3,05493266	yes	X
5	56	customer	7,8635688	7,39725814	15,2608269	6,90471671	no	recovered
6	73	customer	5,42524432	16,1922174	21,6174618	5	yes	X
7	42	worker	3,78407818	6,09197388	9,87605207	0	no	recovered
8	79	customer	7,64336265	15,6184986	23,2618612	5,81350262	yes	X
9	64	customer	10,0744156	13,9278301	24,0022457	0	no	X
10	68	customer	8,44960472	9,14038875	17,5899935	5,60345425	no	recovered
11	42	customer	3,76460927	12,758779	16,5233883	0	no	recovered
12	61	customer	8,29408132	15,6969609	23,9910423	5,52352788	yes	X
13	53	worker	8,05222966	7,91342864	15,9656583	6,51075926	yes	recovered

NOTE !!! : COULD YOU PLEASE ANSWER IT USING MINITAB (also with the steps(procedure) you click in minitab)

Is there a relationship between incubation period and hospitalization period? Comment using graphs and statistical proofs by calculating the correlation coefficient.

Is there a relationship between total infection period vs. age and market encounter of patients? Comment using graphs and statistical proofs. What is the relationship equation and how much of the variation is explained by the model?

Answer 1

Analyzing the above data using MINITAB

Step1 Enter the data into the MINITAB

Is there a relationship between "Incubation Period" and "Hospitalization Period"

This we will be checking using the graphs and correlation coefficient.

MINITAB > Stat > BAsic Statistics > Correlation

Above highlighted is the required correlation.Which is not that much significant and also can be judged by using p-value(0.541>0.05)

For graph we can draw Scatter plot

MINITAB > Graph > Scatter PLot (select the appropriate variables) > Press "OK"

This graph also shows that not having significant correlation.

B) It Is asked to check the relationship between total infection period vs. age and market encounter of patients.

And also what is the relationship equation and how much of the variation is explained by the model?

I.e we have to run the regrssion of Total infection period on (age and market encounter patients) and make the conclusion.

MINITAB > Stat > Regression > Fit Regression line > Select proper y and x's and press "OK"

MINITAB OUTPUT

Regression Analysis: total infection time versus age, market encounter Method Categorical predictor coding (1, 0) Analysis of Variance Source DF Adj SS Adj MS F-Value P-Value Regression 2 113.62 56.81 5.57 0.024 age 1 14.43 14.43 1.41 0.262 market encounter 1 37.62 37.62 3.69 0.084 Error 10 102.01 10.20 Total 12 215.62 Model Summary S R-sq R-sq(adj) R-sq(pred) 3.19387 52.69% 43.23% 18.85% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 14.91 4.86 3.07 0.012 age 0.0827 0.0695 1.19 0.262 1.45 market encounter worker -4.87 2.54 -1.92 0.084 1.45 Regression Equation market encounter customer total infection time = 14.91 + 0.0827 age worker total infection time = 10.04 + 0.0827 age 

Also it is asked that how much of the variation is explained by the model?

Answer:- R-square=52.69 % of variation in the total infection timeis explained by model.