Question

I need a regression analysis done on the following numbers.

IC	Price	Income	Temp	Lag-temp
0.386	0.27	78	41	56
0.374	0.282	79	56	63
0.393	0.277	81	63	68
0.425	0.28	80	68	69
0.406	0.272	76	69	65
0.344	0.262	78	65	61
0.327	0.275	82	61	47
0.288	0.267	79	47	32
0.269	0.265	76	32	24
0.256	0.277	79	24	28
0.286	0.282	82	28	26
0.298	0.27	85	26	32
0.329	0.272	86	32	40
0.318	0.287	83	40	55
0.381	0.277	84	55	63
0.381	0.287	82	63	72
0.47	0.28	80	72	72
0.443	0.277	78	72	67
0.386	0.277	84	67	60
0.342	0.277	86	60	44
0.319	0.292	85	44	40
0.307	0.287	87	40	32
0.284	0.277	94	32	27
0.326	0.285	92	27	28
0.309	0.282	95	28	33
0.359	0.265	96	33	41
0.376	0.265	94	41	52
0.416	0.265	96	52	64
0.437	0.268	91	64	71

Answer 1

analysis:

The dependent variable is temperature. The independent variables are ic, price, income, and lag temperature.

The regression equation is given by: temp = 40.63+ 73.079*IC + 22.57*Price - 0.6156*Income + 0.56*lag-Temp

there is 78% variation in the temperature which is explained by all independent variables in the model namely ic, price, income, and lag temperature.

The null hypothesis, the model is not significant. Versus the alternative hypothesis, the model is significant. With (F=22.1259, P<5%), the null hypothesis is rejected at 5% level of significance and I can conclude that the model is significant.

hoi: betai = 0. beta_i is not significant. Versus the alternative hypothesis, betai =/= 0. beta_i is significant. With p<5%, I reject the null hypothesis at 5% level of significance and conclude that the coefficient of income and lag temperature is significant. With p>5%, I fail to reject the null hypothesis and conclude that the coefficient of ic and price is not significant.

with one unit increase in IC, the value of temperature is increased by 73 degrees. With $1 increase in price, the value of temperature is increased by 22.57 degrees. but this value is not significant at 5% level of significance.

With $1 increase in income, the value of temperature is decreased by . 1 degree. With one degree increase in the lag temperature, II is the value of temperature is increased by 0.56 degree. this value is significant at 5% level of significance.

steps:

data -> data analysis -> regression

output: