Bertelsmann Udacity Data Science Scholarship Notes
Learn by writing! Read, write, read, write. Read all the stuff once and write down the main ideas. “When you write down your ideas you automatically focus your full attention on them. Few if any of us can write one thought and think another at the same time. Thus a pencil and paper make excellent concentration tools.”
Take lots of breaks! Once every 30 minutes it’s good to take a break and do something different. You can eat, take a glass of water, listen to a song, etc. In this way, you will remember the matter according to the actions you made in the pause: Before drinking water, we learn about x before we eat learn about y. Make as many as possible!
Learn by learning others! Many complicated things can be learned quickly if you try to explain it to someone while you don’t master the subject yet. It sounds paradoxical but the explanation is simple: Trying to explain a complicated thing in simple words like a 7-year-old child, your mind is quick to remember the basic things.
Use colors! Visual memory is very important. Color each of your main ideas and try to use more colors when you write your notes.
Below are my Bertelsmann Udacity Data Science Scholarship flashcards for lesson 1 to 3 that helped me a lot during this past weeks and hope maybe it will be of great help to you too.
A construct is anything that is difficult to measure because it can be defined and measured in many different ways.
Example: Volume is a construct. We know volume is the space something takes up but
we haven’t defined how we are measuring that space. (i.e. liters, gallons, etc.)
In an experiment, the manner in which researchers handle subjects is called a treatment. Researchers are specifically interested in how different treatments might yield differing results.
Something given to subjects in the control group so they think they are getting the treatment, when in reality they are getting something that causes no effect to them.
Example: a sugar pill
The group of a study that receives varying levels of the independent variable. These groups are used to measure the effect of a treatment.
The dependent variable of a study is the variable that experimenters choose to measure during an experiment; it is usually situated along the y-axis of a graph.
The operational definition of a construct is the unit of measurement we are using for the construct. Once we operationally define something it is no longer a construct.
Example: Minutes is already operationally defined; there is no ambiguity in what we are
The independent variable of a study is the
variable that experimenters choose to manipulate; it is usually situated along the x-axis of a graph.
An observational study is when an experimenter watches a group of subjects and does not introduce a treatment.
Example: A survey is an example of an observational study
The population is all the individuals in a group.
Example: The mean of a population is defined with the symbol µ whereas the mean of a sample is defined as ¯x
In statistics, you’ll be working with samples. A sample is just a part of a population.
Example: if you want to find out how much the average American reads, you aren’t going to want to survey everyone in the population, so you would choose a small number of people in the population.
Parameter vs Statistic
A parameter defines a characteristic of the
population whereas a statistic defines a characteristic of the sample.
The group of a study that receives no treatment. This group is used as a baseline when comparing treatment groups.
Blinding is a technique used to reduce bias. Double blinding ensures that both those administering treatments and those receiving treatments do not know who is receiving which treatment.
In statistics, the frequency ( or absolute frequency) of an event is the number of times the event occurred in an experiment or study. These frequencies are often graphically represented in histograms.
A proportion describes the share of one value for a variable in relation to a whole.
It’s calculated by dividing the number of times a particular value for a variable has been observed, by the total number of values in the population.
A visualization showing how a set of quantitative values are distributed across the range of values. The X-axis (across the bottom) are the values of the variable (in intervals). The Y-axis (vertically) is for frequency or proportions.
Skewed distributions are distributions in which one of the tails of the distribution is pulled away from the center. The tail goes to the right or to the left.
Positively skewed distribution
A positively skewed distribution is a distribution where the tail of the distribution extends to the right.
Negatively skewed distribution
A negatively skewed distribution is a distribution where the tail of the distribution extends to the left.
Central tendency refers to the middle value or perhaps a typical value of the data and is measured using the mean, median and mode.
How do we calculate the mean?
The median is the middle score of all the scores in a sample when the scores are arranged in ascending order. How do we calculate the median?
The most common value in a set of measurements.