Stat descriptive

Définition du local

## 
## Call:
## lm(formula = prix ~ budget_alim, data = bdd_vin)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -9.366 -5.609 -3.075  3.103 17.925 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 12.65653    1.79784   7.040 2.58e-11 ***
## budget_alim -0.01164    0.03890  -0.299    0.765    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8.282 on 214 degrees of freedom
## Multiple R-squared:  0.000418,   Adjusted R-squared:  -0.004253 
## F-statistic: 0.08948 on 1 and 214 DF,  p-value: 0.7651

## 
## Call:
## lm(formula = prix ~ budget_alim, data = bdd_pomme)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.5243 -0.8225 -0.0243  0.5784  4.6775 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  3.82699    0.33831  11.312   <2e-16 ***
## budget_alim -0.01009    0.00732  -1.378     0.17    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.559 on 214 degrees of freedom
## Multiple R-squared:  0.0088, Adjusted R-squared:  0.004168 
## F-statistic:   1.9 on 1 and 214 DF,  p-value: 0.1695

Selection consentement à payer pour le vin

Distribution selon caractéristique

Comparaison de moyenne

Comparaison BIO vs non BIO

## 
##  Welch Two Sample t-test
## 
## data:  prix by bio
## t = 0.11089, df = 213.46, p-value = 0.9118
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -2.097019  2.347019
## sample estimates:
## mean in group 0 mean in group 1 
##        12.20833        12.08333

Comparaison Local vs non Local

## 
##  Welch Two Sample t-test
## 
## data:  prix by local
## t = 1.5236, df = 213.99, p-value = 0.1291
## alternative hypothesis: true difference in means between group 0 and group 1 is not equal to 0
## 95 percent confidence interval:
##  -0.5017635  3.9184302
## sample estimates:
## mean in group 0 mean in group 1 
##        13.00000        11.29167

Déterminants du consentement à payer

## 
## Call:
## lm(formula = prix ~ local + bio + sexe + budget_alim, data = bdd_vin)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -10.024  -5.713  -3.061   3.130  19.074 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 13.53782    1.97040   6.871 7.06e-11 ***
## local       -1.70833    1.12837  -1.514    0.132    
## bio         -0.12500    1.12837  -0.111    0.912    
## sexeHomme    0.53452    1.18597   0.451    0.653    
## budget_alim -0.01557    0.03991  -0.390    0.697    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8.292 on 211 degrees of freedom
## Multiple R-squared:  0.01216,    Adjusted R-squared:  -0.006569 
## F-statistic: 0.6492 on 4 and 211 DF,  p-value: 0.628

Representation des effets marginaux

Déterminant du consentement à payer Pomme

Distribution selon caractéristique

Déterminants du consentement à payer

## 
## Call:
## lm(formula = prix ~ local + bio + sexe + budget_alim, data = bdd_pomme)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.9456 -0.6556  0.0574  0.7942  4.1449 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  4.081259   0.358755  11.376  < 2e-16 ***
## local       -0.447222   0.205445  -2.177 0.030602 *  
## bio          0.038889   0.205445   0.189 0.850047    
## sexeHomme   -0.757058   0.215932  -3.506 0.000556 ***
## budget_alim -0.004523   0.007266  -0.622 0.534295    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.51 on 211 degrees of freedom
## Multiple R-squared:  0.08297,    Adjusted R-squared:  0.06559 
## F-statistic: 4.773 on 4 and 211 DF,  p-value: 0.001048