Quantitative Methods occupies a 12% weight in **CFA Level 1 Syllabus**. The PDF file of Quantitative Methods was contributed by Prof.Mince. In our previous article, we have already made available **PDF Notes for Derivatives**. Quants is the easiest subject in CFA level 1. The Key to scoring high marks in Quantitative Methods is practising lots of questions, which gives you immense confidence.

**CFA Level 1 Quantitative Methods PDF**

Quantitative Methods Formula Notes PDF | Download |

Probability PDF Notes | Download |

Sampling in Quantitative Methods PDF | Download |

Hypothesis in Quantitative Methods PDF | Download |

TMV in Quantitative Methods PDF | Download |

**Techniques in Quantitative Methods **

**Risk solvers**– allows you to solve equations with a lot a variables and unknowns**Cost Benefit analysis**– Helps us determine if an investment is worth it or not**ensitivity analysis –**Helps us visualize what happens to say, profits based on varying circumstances. For example what happens to profits if revenues grow at 5%, 10%, 15% etc. per year. What happens to costs if interest rates on a bank loan go up by 1% etc.

**Descriptive Statistics : Quantitative Methods**

Descriptive statistics are often used to describe variables. Descriptive statistics are performed by analyzing one variable at a time (univariate analysis). All researchers perform these descriptive statistics before beginning any type of data analysis

**Frequency Tables : Quantitative Methods**

Frequency tables are a detailed description of the categories/values for one variable. A frequency table most often includes all of the following:

- Absolute frequency (or just frequency)
- Relative frequency (or percent)
- Cumulative frequency
- Crosstabulations

**Dependent Variable : Quantitative Methods**

If you are looking to explain a variable using one or more variables then you want to use any of methods described below depending on the level of measurement of the dependent variable.

Note that for all of the models described below, you can never have a nominal variable (with ore than two categories) as in independent variable.

If you want to use a nominal level variable as an IV, then you must recode it into one or more dummy variables. Suppose you wanted the model to control for race.

Since race is a nominal variable you cannot include it in your analysis as an IV, however, you could create dichotomous variables for all the categories of race and include these newly formed dichotomous variables.

**Closing Note : Quantitative Methods PDF**

The PDF Notes on Quantitative Methods were provided only for educational purposes and recommend users to avoid using the content for any commercial means.

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