# Math Study

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Math Study

## 1. Unit 1

### 1.1. Representation

1.1.1. Histogram

1.1.1.1. x: intervals

1.1.1.2. y: frequency

1.1.2. Box Plot

1.1.2.1. 5# summary (min, Q1, med, Q3, max)

1.1.3. Stem and Leaf

1.1.3.1. stem + leaf table

### 1.2. Analysis

1.2.1. center

1.2.1.1. mean

1.2.1.2. median

1.2.2.1. IQR

1.2.2.2. Range

1.2.2.3. deviation (standard, population)

1.2.3. shape

1.2.3.1. symmetrical

1.2.3.2. skewed

1.2.3.3. uniform

1.2.3.4. single/double peak

1.2.4. Outliers

1.2.4.1. 1.5 x IQR

### 1.3. Interpretation

1.3.1. Low IQR/range/deviation → consistent

1.3.2. Stating a subjective opinion based on the analysis of the data

## 2. Unit 2

### 2.1. Representation

2.1.1. Scatterplot

2.1.2. LSRL

2.1.2.1. y=a+bx

### 2.2. Analysis

2.2.1. Strength

2.2.1.1. correlation coefficient (r)

2.2.1.2. R^2 (variability)

2.2.2. Outliers

2.2.3. Direction

2.2.3.1. slope

2.2.3.2. y intercept

2.2.4. Form

2.2.4.1. residual plot

### 2.3. Interpretation

2.3.1. r^2

2.3.1.1. put in percent

2.3.1.2. __% of the variability of the number of (y variable) can be explained by a linear relationship with the (x variable) the other __% can be explained by other factors such as _______

2.3.1.3. close to 1 = strong relationship

2.3.2. slope

2.3.2.1. For every increase of (x variable) we expect the (y variable) to increase/decrease by (slope)

2.3.3. y intercept

2.3.3.1. when (x variable) is 0, we expect the (y variable) to be _____. This does/doesn't make sense because ______.

2.3.4. r

2.3.4.1. the strength of the correlation is (strong/weak) because it is/isn't close to 1.

2.3.5. residual plots

2.3.5.1. Based on the residual plot, a linear form is/isn't appropriate because of the random scatter.

2.3.5.2. OUTLIERS