【ML】Basic terminology -- 2

In a statistical test, the things failed for a lot of different reasons……

Hypothesis testing: In statistical lingo, the idea of trying to determine if these drugs are the same or not is called Hypothesis Testing.

Statistical hypothesis test: Is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis.

Null hypothesis: The hypothesis that there is no difference between things is called the Null Hypothesis.

Null hypothesis significance testing:

1. NHST is a method of statistical inference by which an experimental factor is tested against a hypothesis of no effect or no relationship based on a given observation.

2. A Null-Hypothesis Statistical Test (NHST, sometimes Null Hypothesis Significance Test), is a statistical procedure in which a null hypothesis is posed, data related to it is generated and the level of discordance of the outcome with the null hypothesis is assessed using a statistical estimate.

P-value(probability value):

1. Helps us to decide if we should reject the Null hypothesis or not. It tells you how likely it is that your data could have occurred under the null hypothesis.

2. The p-value is a proportion between 0 and 1, the closer a p-value is to 0, the more confidence we have that Drug A and Drug B are different. P-value cannot tell use how difference the drug can be.

3. In practice, a commonly used threshold is 0.05. (It means that if there is no difference between Drug A and Drug B, then only 5% of those experiments would result in the wrong decision.)

4. A p-value is the probability that random chance generated the data or something else that is equal or rarer.(If the data is continuous, using a "density".)

False positive: Getting a small p-value when there is no difference is called False Positive.

Pearson's correlation: Indicate the relation between the x-axis and y-axis. Quantifies the strength of relationships.

R-squared

R

Covariance

generalization performance

目标函数

Reference:

P-value:

https://m.youtube.com/watch?v=vemZtEM63GY

https://m.youtube.com/watch?v=5Z9OIYA8He8