I am so sorry, I am beginner in statistic analysis, I have project using R to analyze the correlation between dependent variables and independents variables.
In this case I have two dependent variables (1. Extrovert, 2. Introvert). And the independent variables i have the data from (Call Log-> how long they call everyday, how many they call everyday, SMS log-> how length text in SMS body every day, how many they sent/received sms for each day).
I am so confused how I can do it, please anyone can give me some good references about it. I also have some questions such as :
- I use the different type of variables, independent variables (data type : numeric) but dependent variable (data type is categorical), so it is possible to apply logistic regression and Pearson?
- Or any someone will give me some advice the better solution such as another methods for solving this problem.
The example of data from dput()
structure(list(sumcallin = c(462L, 998L, 335L, 179L, 34L, 0L, 0L, 0L, 0L, 0L), caountcallin = c(7L, 5L, 8L, 5L, 1L, 1L, 0L, 1L, 1L, 1L), sumcallout = c(1068L, 81L, 519L, 393L, 342L, 0L, 583L, 1902L, 358L, 1017L), countcallout = c(15L, 3L, 10L, 5L, 6L, 0L, 3L, 3L, 3L, 3L), sumreceived = c(322L, 75L, 20L, 35L, 8L, 35L, 135L, 103L, 471L, 173L), countreceived = c(15L, 4L, 2L, 3L, 1L, 2L, 7L, 3L, 18L, 5L), sumsent = c(171L, 31L, 25L, 23L, 8L, 55L, 87L, 9L, 400L, 258L), countsent = c(10L, 4L, 1L, 3L, 1L, 3L, 4L, 1L, 13L, 8L), personality = structure(c(2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L), .Label = c("extro", "intro"), class = "factor")), .Names = c("sumcallin", "caountcallin", "sumcallout", "countcallout", "sumreceived", "countreceived", "sumsent", "countsent", "personality"), row.names = c(1L, 2L, 3L, 4L, 5L, 37L, 38L, 39L, 40L, 41L), class = "data.frame")
Thank you for your help.
1. Extrovert, 2. Introvertare the two categories that your outcome (dependent) variable can take on. Is that correct? Are you trying to predict whether a new row is