Symbol and Pronunciation Key



Symbol and Pronunciation Key

|Chapter |Symbol |Meaning |Pronunciation |

| | | | |

|2: Presenting Data in Tables and Charts | | | |

| | | | |

|3:Summarizing and Describing Numerical | | | |

|Data | | | |

| |N |Population size | |

| |n |Sample size | |

| |μ |Population Mean |mu |

| |Σ |Operation of Adding |sigma or sum |

| |ΣX |Adding a group of values |sigma X or sum of X |

| |[pic] |Sample mean |X bar |

| |(2 |Population variance |sigma squared |

| |( |Population standard deviation |sigma |

| |S |sample standard deviation | |

|4: Basic probability | | | |

| |P(A) |Probability of A |P of A |

| |P(A and B) |Probability of A and B |P of A and B |

| |P(A or B) |Probability of A or B |P of A or B |

| |P(A|B) |Probability of A given B has happened |P of A given B |

| | | | |

|5: Discrete Probability Distributions |n! |n times n-1 times n-2 ….. |n factorial |

| |[pic] |the number of ways to choose x objects from a group of |n combination x |

| | |n objects | |

| | | | |

|6: Normal Distribution and Sampling | | | |

|Distributions | | | |

| |[pic] |Mean of the distribution of sample means |mu x bar |

| |[pic] |Population standard error of the sample means |sigma x bar |

| |p |Population proportion | |

| |ps |Sample proportion |p sub s |

| | | | |

|7: Confidence Interval Estimation | | | |

| |( |Level of significance |alpha |

| |E |Margin of error |e |

| |d.f. |Degrees of freedom | |

| | | | |

| | | | |

|8: Hypothesis Testing, One-Sample Tests | | | |

| |H0 |Null hypothesis |H 0 |

| |H1 |Alternative hypothesis |H 1 |

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|9: Two-Sample Tests | | | |

| |n1 |Number of observations in sample 1 |n 1 |

| |n2 |Number of observations in sample 2 |n 2 |

| |[pic] |Mean from first sample |x bar 1 |

| |[pic] |Mean from second sample |x bar 2 |

| |[pic] |Pooled sample variance |s squared p |

| |(D |Population mean of the difference between dependent | |

| | |samples | |

| |[pic] |Sample mean of the difference between dependent samples|d bar |

| |[pic] |Sample variance of the difference between dependent |s squared d |

| | |samples | |

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|10: ANOVA | | | |

| |MSA |Mean square among groups | |

| |MSW |Mean square within groups | |

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|12: Simple Regression and Correlation | | | |

| |(0 |Population intercept |beta 0 |

| |(1 |Population slope |beta 1 |

| |b0 |Sample intercept |b 0 |

| |b1 |Sample slope |b 1 |

| |[pic] |Standard error of the slope |s b 1 |

| |r2 |Coefficient of determination |r square |

| |SYX |Standard error of the estimate | |

| |SST |Total sum of squares | |

| |SSR |Regression sum of squares | |

| |SSE |Error sum of squares | |

| |MSR |Mean square regression | |

| |MSE |Mean square error | |

| |DW |Durbin-Watson statistic | |

| |[pic] |Predicted value of the dependent variable |y hat |

| |( |Population correlation coefficient |rho |

| |r |Sample correlation coefficient | |

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|13: Multiple Regression | | | |

| |VIF |Variance inflation factor | |

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