Hi. I'm doing a project related to face care where I have to find the relation between two categorical variables (gender (with F and M values) and type of product (normal skin, purifying, anti-age, hydrating, sensitive skin, other)).

I used the code `gender_impact <- face_prod ~ gender `

and `summary(lm(gender_impact))`

but it gives me the error "Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf in 'y'"

How can I solve this?

UPDATE:

The code i wrote is:

```
face_prod <- factor(beauty$`type of face care prod`)
gender <- factor(beauty$Gender)
gender_impact <- face_prod ~ gender
model1 = glm(gender_impact, data=beauty, family=binomial)
summary(model1)
```

And the result is:

Call:

glm(formula = gender_impact, family = binomial, data = beauty)

Deviance Residuals:

Min 1Q Median 3Q Max

-1.7642 0.6884 0.6884 0.6884 0.6884

Coefficients:

Estimate Std. Error z value Pr(>|z|)

(Intercept) 1.3193 0.2167 6.089 1.13e-09 ***

genderM 15.2468 1385.3778 0.011 0.991

Signif. codes: 0 ‘* ’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

Null deviance: 133.29 on 130 degrees of freedom

Residual deviance: 131.89 on 129 degrees of freedom

AIC: 135.89

Number of Fisher Scoring iterations: 15

So what can I conclude? Are they related? What are the values I have to look at to understand it?