Statistics Canon: Statistics and Math Symbols

神掌打通任督二脈‧易筋經以簡馭繁

符號意義:統雄快訣統雄快訣 延伸閱讀延伸閱讀 進階議題進階議題 警示訊息警示訊息

統計常用符號與其英語讀法

數學常用符號與其英語讀法

統計神掌易筋經

統計與理論建構


統計常用符號與其英語讀法

Pronunciations of Statistical Symbols

Relational Symbols
  =   equals
is the same as
     is not equal to
is different from
  >   is greater than
is more than
exceeds
is above
  
or >=  
is greater than or equal to
is at least
is not less than
  <   is less than
is fewer than
is below
  
or <=  
is less than or equal to
is at most
does not exceed
is not greater than
is no more than
A < x < B x is between A and B, exclusive
A ≤ x ≤ B x is between A and B, inclusive
A ≅ B A is approximately equal to B

Here are symbols for various sample statistics and the corresponding population parameters. They are not repeated in the list below.

sample
statistic
population
parameter
description
“x-bar” μ “mu”
or μx
mean
M
(TIs say Med)
(none) median
s
(TIs say Sx)
σ “sigma”
or σx
standard deviation
For variance, apply a squared symbol (s² or σ²).
r ρ “rho” coefficient of linear correlation
“p-hat” p proportion
zo   to   χ²o (n/a) calculated test statistic

μ and σ take subscripts to show what you are taking the mean or standard deviation of. For instance, σ (“sigma sub x-bar”) is the standard deviation of sample means, or standard error of the mean.

Other symbols — Roman letters

  • b = y intercept of a line (Some statistics books use b0.)
  • CLT = Central Limit Theorem
  • d = difference between paired data
  • df or ν “nu” = degrees of freedom in a Student’s t or χ² distribution
  • E = margin of error, a/k/a maximum error of the estimate
  • f = frequency
  • f/n = relative frequency
  • Ho = null hypothesis
  • H1 or Ha = alternative hypothesis
  • IQR = interquartile range, Q3−Q1
  • m = slope of a line (The TI-83 uses a and some statistics books use b1.)
  • n = sample size, number of data points, or number of trials in a probability experiment
  • p = probability value. In binomial probability distributions p is the probability of “success” (however defined) on any one trial and q = 1−p is the probability of “failure” (the only other possibility) on any one trial.
    In hypothesis testing, p is the calculated p-value, the probability that rejecting the null hypothesis would be a wrong decision. In tests of population proportions, p stands for population proportion and for sample proportion (see table above). You have to rely on context to know what “p” means.
  • P(A) = the probability of event A. (Sometimes P′(A) is used to distinguish the experimental probability of event A from the theoretical probability.)
  • P(AC) = probability of not-A, the probability that A does not happen
  • P80 or P80 = 80th percentile (Pk or Pk = k-th percentile)
  • Q1 or Q1 = first quartile (Q3 or Q3 = third quartile)
  • = coefficient of determination
  • SEM = standard error of the mean (symbol is σ)
  • SEP = standard error of the proportion (symbol is σ)
  • x = a variable or a data value (raw score). As a column heading, x means a series of data values.
  • ŷ “y-hat” = predicted average y value for a given x, found by using the regression equation
  • z = standard score or z-score. Using the individual score x, the mean μ, and the standard deviation σ, the formula is z equals (x-bar minus mu) over sigma
    Using a sample mean and comparing it to the distribution of sample means, the formula is z equals (x-bar minus mu) over (sigma over square root of n)
  • z(area) or zarea = the z-score, such that that much of the area under the normal curve lies to the right of that z. This is not a multiplication!

Greek letters (see also the table above):

  • α “alpha” = significance level in hypothesis test, or acceptable probability of a Type I error (probability you can live with); 1−α = confidence level
  • β “beta” = in a hypothesis test, the acceptable probability of a Type II error; 1−β is called the power of the test
  • σ “sigma-sub-x-bar” = standard error of the mean (abbreviated SEM)
  • σ “sigma-sub-p-prime” = standard error of the proportion (abbreviated SEP)
  • “sigma” = summation. (This is upper-case sigma. Lower-case sigma means standard deviation of a population; see the table above.) Be careful with the order of operations, such as ∑x² versus (∑x)².
  • χ² “chi-squared” = distribution for multinomial experiments and contingency tables

數學常用符號與其英語讀法

Pronunciations of Mathematical Symbols

引用自 UEfAP (Using English for Academic Purposes: A Guide for Students in Higher Education)。

[Literature/!DataAnalysis/Pronunciation of mathematical symbols.html]

來源與參考連結 Source and Related Links

http://www.tc3.edu/instruct/sbrown/ti83/normcalc.htm

http://cnx.org/content/m16302/latest/

http://www.statistics.com/uploads/statsymbols.pdf

http://www.rapidtables.com/math/symbols/Statistical_Symbols.htm

http://stattrek.com/statistics/notation.aspx

http://www.uefap.com/speaking/symbols/symbols.htm

回頁首 Up to page head 至頁尾 Down to page bottom
上一頁 Back to previous page 回頁首 Up to page head 下一頁 Go to nex page  

統雄數學神掌系列目錄
分享意見反映
統計教學的內涵與取向
高考統計考題的解析
微積分精華篇
微積分思想篇
微積分進階精華篇
統計/數學符號與其英語讀法
資料型態與視覺呈現
敘述統計
機率論與機率分配
推論統計學精華篇
t分配與 t檢定
推論統計‧理論建構
資料分析程序與SPSS基礎
SPSS 資料清理
SPSS 轉換:Recode 重新編碼
SPSS 轉換:Compute 建構新變項
SPSS 選擇觀察值_SPSS 資料庫管理
樣本代表性檢定
單變項:類別_二元資料/百分比分析-詮釋
單變項:類別_二元資料/百分比推論-應用
單變項分析:連續資料_描述與估計推論
單變項連續資料的視覺檢視:變項清理與啟發
卡方分析(雙向)
多向卡方分析
列聯表樞紐分析
單向卡方分析
變異數分析(單因子):詮釋
變異數分析(單因子):應用
簡單迴歸/相關分析:詮釋
簡單迴歸/相關分析:應用
對數/邏輯相關分析
測量工具信度/效度分析
量表信度 檢定
量表效標關聯效度 檢定
探索式因素分析 (EFA):詮釋與實作
探索式因素分析 (EFA):應用進階
因素效度分析_CFA:詮釋
因素效度分析_CFA:應用
多變項分析精華篇
多元迴歸分析:詮釋
多元迴歸分析:應用
一般線性模型精華篇
廣義線性模型
雙因子/多因子變異數分析
調節模型與交互作用詮釋
調節模型分析與建構
SPSS 統計圖應用:調節模型檢定
共變數分析/詮釋
共變模型建構/應用
因果模型與因果邏輯
中介模型分析
因徑/SEM:模型詮釋與因果邏輯
因徑/SEM:探索式因徑模型建構
因徑/SEM:驗證式結構方程解析
多變項分析實例SEM
多變項分析實例SEM+調節篇
因徑/結構方程SEM:反省
無母數統計
統計研討篇
專題-卜豐投針實驗
專題-機率與統計悖論
1類知識計量工具
2類知識計量工具
3類知識計量工具
非等機率知識體系建構
TX空時座標建構
一般取用測量
信仰取用測量
研究方法/民調市調系列
請點這裡看所有留言分類 Please click here to view categories of comments
同類別內相關主題