Karteikarten
Statistics
Karten in diesem Stapel (28)
- 1What is statistics? Name 4 StepStep 1 - Producing Data (Collecting Data)
Step 2 - Exploratory Data Analysis
Step 3 - Calculating Probability
Step 4 - Inferring (Inferential Statistic) - 2DataData are pieces of information about individuals organized into variables.
- 3Descriptive StatisticsMethods for summarizing and
organizing the data
(EAP = Exploratory Data Analysis) - 4Individual vs VariableIndividual: Who we are getting the data from. Source of information
Variable: Characteristic of individual or object - 5Types of variablesQuantitative & Qualitative (Categorical)
- 6Qualitative Variable (Categorical)A variable that can be classified into categories. If numbers are included these don't have a numerical value.
- 7The distribution of a categorical variable is summarized using:Graphical Display (Pie Charts and Bar Charts)
Numerical Summaries: Counts and percentages - 8PictogramA pictogram is a variation on pie charts and bar charts. Pictograms can be misleading, so make sure to use a critical approach when interpreting the information the pictogram is trying to convey.
- 9Quantitative VariableA variable that can be measured, has numerical value, and represents some kind of measurement
- 10Types of Quantitative Variable- Discrete: Finite, Countable, 1full separation point between numbers.
- Continuous: Infinite values, Not countable, Can be broken down into infinite parts: decimals, temperature, time, distance, etc. Continuous form - 11Frequency Distribution/ChartTable where we calculate the different values (categories) and how many times each value occurs (count)
- 12Frequency & The Relative FrequencyFrequency (count) refers to the number of observations in each category.
A relative frequency of a qualitative variable is its frequency divided by the sample size (percentage) - 13Pie Chart & Bar GraphPie Chart: he pie chart emphasizes how the different categories relate to the whole
Bar Graph: emphasizes how the different categories compare with each other - 14HistogramUsed for quantitative data only because the columns are connected to each other’s in representation of potential infinite numbers. In a histogram, you break the range of values into intervals (bins or classes) and count how many observations fall into each interval.
- 15What is the difference between the following: a - (70 - 80) b - [70 - 80] c - (70 - 80] d - [70 - 80)a - Doesn't include 70 nor 80
b - Includes 70 and not 80
c - Doesn't include 70 but includes 80
d - Includes 70 and not 80 - 16Stem - leaf plotThe stemplot (also called stem and leaf plot) is another graphical display of the distribution of quantitative data.
- 17How do you divide the intervals?You calculate the range of the interval by selecting a number that makes sense for your calculation. Example: 10's if its scores, 5 if the data is best divided by 5, etc
- 18What's included on the x axis vs the. y axis?To construct the histogram, we plot the intervals on the X-axis, and show the number of observations in each interval (frequency of the interval) on the Y-axis, which is represented by the height of a rectangle located above the interval
- 193 Measures of centerMean, Median, Mode
- 20Meanx bar =
- 21IQRThe Inter Quartile Range measures the variability of a distribution by giving us the range covered by the MIDDLE 50% of the data.
- 22Sampling Framev
- 23Probability Sampling planv
- 24observational studyin which values of the variable or variables of interest are recorded as they naturally occur. There is no interference by the researchers who conduct the study.
- 25sample surveywhich is a particular type of observational study in which individuals report variables' values themselves, frequently by giving their opinions.
- 26experimentInstead of assessing the values of the variables as they naturally occur, the researchers interfere, and they are the ones who assign the values of the explanatory variable to the individuals. The researchers "take control" of the values of the explanatory variable because they want to see how changes in the value of the explanatory variable affect the response variable.
- 27Prospective Studythe values of the variables of interest (TV watching and snack consumption) are recorded forward in time.
- 28Retrospective observational study.the values of the variables of interest are recorded backward in time.
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- Mathematics Karteikarten am Statistics, erstellt von Ana Peña am 15/06/2021.
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- Ana Peña
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