統計テスト コードの助けが必要です。基本的に私は、年齢、政治的地位、大麻合法化に対する見解の関係を研究しようとしています. このデータセットは、2010 年の英国の社会的態度に関する調査です。
bsa_2010 <- read.csv("https://dl.dropboxusercontent.com/s/ubl9huokroj9jw8/bsa%202010.csv")
> dput(head(bsa_2010))
structure(list(Country = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("England",
"Scotland", "Wales"), class = "factor"), RSex = structure(c(1L,
1L, 2L, 2L, 2L, 1L), .Label = c("Female", "Male"), class = "factor"),
RAge = c(75L, 34L, 81L, 25L, 33L, 76L), MarStat = structure(c(4L,
4L, 2L, 3L, 3L, 5L), .Label = c("Living as married", "Married",
"Not married", "Separated or divorced after marrying", "Widowed"
), class = "factor"), ChildHh = structure(c(1L, 1L, 1L, 1L,
1L, 1L), .Label = c("No", "Yes"), class = "factor"), WhPaper = structure(c(8L,
8L, 8L, 11L, 12L, 8L), .Label = c("(Scottish) Daily Express",
"(Scottish) Daily Mail", "Daily Mirror/ Scottish Mirror",
"Daily Record", "Daily Star", "Daily Telegraph", "Financial Times",
"Skip,not read paper normally", "The Guardian", "The Independent",
"The Sun/ Scottish Sun", "The Times"), class = "factor"),
PartyIDN = structure(c(2L, 7L, 2L, 6L, 2L, 6L), .Label = c("British National Party (BNP)/ National Front",
"Conservative", "Don't know", "Green Party", "Labour", "Liberal Democrat",
"None", "Other answer (WRITE IN)", "Other party (WRITE IN)",
"Plaid Cymru", "Refused to say", "Scottish National Party",
"UK Independence Party (UKIP)/Veritas"), class = "factor"),
Partyid1 = structure(c(2L, 7L, 2L, 6L, 2L, 6L), .Label = c("British National Party (BNP)/ National Front",
"Conservative", "Don't know", "Green Party", "Labour", "Liberal Democrat",
"None", "Other answer", "Other party", "Plaid Cymru", "Refusal",
"Scottish National Party", "UK Independence Party (UKIP)/Veritas"
), class = "factor"), PartyId2 = structure(c(1L, 5L, 1L,
4L, 1L, 4L), .Label = c("Conservative", "Green Party", "Labour",
"Liberal Democrat", "None", "Other party", "Other/DK/Ref"
), class = "factor"), Spend1 = structure(c(3L, 4L, 4L, 3L,
3L, 4L), .Label = c("(None of these)", "Defence", "Education",
"Health", "Help for industry", "Housing", "Overseas aid",
"Police and prisons", "Public transport", "Roads", "Social security benefits"
), class = "factor"), Spend2 = structure(c(6L, 3L, 2L, 4L,
9L, 10L), .Label = c("(None of these)", "Defence", "Education",
"Health", "Help for industry", "Housing", "Overseas aid",
"Police and prisons", "Public transport", "Roads", "Skip,no 1st priority",
"Social security benefits"), class = "factor"), RClassGp = structure(c(4L,
6L, 1L, 2L, 4L, 6L), .Label = c("Employers in small org; own account workers",
"Intermediate occupations", "Lower supervisory & technical occupations",
"Managerial & professional occups", "Not classifiable", "Semi-routine & routine occupations",
"Skip, never had a job+DK+NA last job"), class = "factor"),
RNSSECG = structure(c(4L, 8L, 9L, 3L, 4L, 8L), .Label = c("1.1",
"1.2", "Intermediate occupations", "Lower managerial and professional occupations",
"Lower supervisory & technical occupations", "Not classified",
"Routine occupations", "Semi-routine Occupations", "Small employers and own account workers"
), class = "factor"), CanLegal = structure(c(1L, 1L, 1L,
2L, 2L, 1L), .Label = c("Taking cannabis should remain illegal",
"should be legal, only licenced shops"), class = "factor"),
RaceOri3 = structure(c(10L, 10L, 10L, 10L, 10L, 10L), .Label = c("ASIAN: of Bangladeshi origin",
"ASIAN: of Chinese origin", "ASIAN: of Indian origin", "ASIAN: of Pakistani origin",
"ASIAN: of other origin (WRITE IN)", "BLACK: of African origin",
"BLACK: of Caribbean origin", "MIXED ORIGIN (WRITE IN)",
"OTHER (WRITE IN)", "WHITE: of any origin"), class = "factor"),
Agecat1 = structure(c(6L, 2L, 7L, 1L, 2L, 6L), .Label = c("(18,28]",
"(28,38]", "(38,48]", "(48,58]", "(58,68]", "(68,78]", "(78,88]",
"(88,98]"), class = "factor"), Agecat2 = structure(c(3L,
1L, 4L, 1L, 1L, 3L), .Label = c("(18,38]", "(38,58]", "(58,78]",
"(78,98]"), class = "factor")), .Names = c("Country", "RSex",
"RAge", "MarStat", "ChildHh", "WhPaper", "PartyIDN", "Partyid1",
"PartyId2", "Spend1", "Spend2", "RClassGp", "RNSSECG", "CanLegal",
"RaceOri3", "Agecat1", "Agecat2"), row.names = c(NA, 6L), class = "data.frame")
使用される変数は次のとおりです。 RAge (年齢) PartyIDN (特定された政党) CanLegal (大麻の合法化)
簡単にするために、年齢をカテゴリに分類し、最大の政党のうち 2 つだけを保持しました。
bsa_2010$Agecat1 <- cut(bsa_2010$RAge, c(18,28,38,48,58,68,78,88,98))
Parties <- subset(bsa_2010, PartyIDN == "Conservative" | PartyIDN == "Labour")
Parties$PartyIDN <- factor(Parties$PartyIDN)
年齢、政治、および大麻合法化に対する人々の見方との関係について P 値を取得するには、どのように統計テストを実行すればよいでしょうか?
どんな助けでも大歓迎です、ありがとう！