Chapter 1: intro to statistics and research design

what are the two branches of statistics??

-descriptive statistics: organize, summarize, and communicate a group of numerical observations, they take large amounts of data

-Inferential statistics: use sample data to make an estimate about the larger popular population, an intelligent guess about the population.

What is descriptive statistics?

for example:

-organize, summarize, and communicate a group of numerical observations, they take large amounts of data,

-For example, taking an average or mean from data a familiar measure length in feet or meters. National Geographic reported on the web that the average great white shark is 15 feet long, or 4.6 meters. And that's just the average; some grow 20 ft to 6 meters. The average length of a great white shark is a descriptive statistic because it describes the lengths of many sharks in just one number.

- A single number reporting the average communicates observations more clearly

What is inferential statistics?

-use sample data to make an estimate about the larger popular population, an intelligent guess about the population

-For example: Researchers from National Geographic got their data and made inferences about shark length even though they did not actually measure every shark, instead, studied a smaller group of sharks to make an intelligent guess about that entire population

population?

is a collection of all possible numbers of a defined group of which we would like to know something

sample?

-is a set of observations from the population of interest

Sample results are used to make inferences about the population

What you want to do is consider what the researcher wants to make inferences about, and who are they making this data on. It's important for selecting different tests statistics

Samples and populations (How to distinguish between the two?)

-for example: The average length of researchers (sample)of great white sharks was used to estimate the average length for the entire world (population) of great white sharks, which was a national geographics interest

Variables?

-Any measurable conditions, events, characteristics, or behaviours that are controlled or observed in a study.

-Research process begins by transforming observations into numbers, researchers use both discrete and continuous numerical observations to quantify variables

when quantifying variables, what are the two different observations we use??

Discrete observation: can only take on specific values and no other values, no other values can exist between these numbers

Continuous observation: can take on a whole range of values, and numbers out to several decimal places, an infinite number of values exist

what is a discrete observation?

-can only take on specific values and no other values, no other values can exist between these numbers

- For example whole numbers: 1,2,3 if we assessed the numbers of great white sightings in a year the only numbers would be whole numbers 95 sharks a year but not 95.5

what is a continuous observation?

-can take on a whole range of values, and numbers out to several decimal places, an infinite number of values exist

- For example, length 1.00cm, 1ox cm and so on, or a person might complete a task in 12.8679 seconds the decimal places are limitless to the decimal places we choose to use

what are the 4 different types of variables in stats that are used in observations????

N.O.I.R

-nominal variables: are used for observations that have categories or names as their values

-ordinal variables: are used for observations that have rankings and order, are always discrete

-interval variables: are used for observations that have numbers in their values, equal distance between pairs of consecutive numbers, is assumed to be equal.

-ratio variable: most complex variable, meet the criteria for interval variables but also have meaningful zero point

what are the two types of observations that are always discrete??

-Nominal variables: are used for observations that have categories or names as their values

- For example: when entering data stats one might code Australians with 1 and New Zealand with 2, in this case, the numbers only identify the category or citizenship for each person. Note that nominal variables are always discrete (whole numbers)

-Ordinal variables: are used for observations that have rankings and order, are always discrete

-For example results of a race, and rankings, cant have intermediate values, a singer could be ranked 1st, 2nd or 3rd, but not 4.5th place

What are the two types of observations that can be continuous??

-interval variables: are used for observations that have numbers in their values, equal distance between pairs of consecutive numbers, is assumed to be equal.

- For example: temperature is an interval variable because the temp from one degree to the next is always the same

- Some interval variables are also discrete variables, such as the number of times one has to get up early each week, this is an interval variable because numerical observations are assumed to be equal

-ratio variables: most complex variable, meet the criteria for interval variables but also have meaningful zero point

-For example weight and lbs, height and cm, zero is meaningful, any ruler measurement is going to be a ratio variable, reaction time in S is a ratio variable, or if someone never has to get up early, then zero is a meaningful observation and could represent a variety of life circumstances.

Statistics programs often refer to both interval numbers and ratio numbers as?

-scale observations, because both interval observations and ratio observations are analyzed with the same statistical tests, specifically

scale variable?

-Is a variable that meets the criteria for an interval variable and a ratio variable

-for example: age and years, have the most amount of information

independent variable?

(X): has at least two levels that we either manipulate or observe to determine its effects on the dependant variable

- For example: if we are studying whether a person's gender predicts a person's attitude about politics, then the independent variable is gender

dependant variable?

(Y)is the outcome variable that we hypothesized to be related to or caused by any changes in the independent variable.

- For example: we hypothesize that the dependent variable is the( attitudes about politics) depending on the independent variable (gender).

By contrast a confounding variable is?

-is any variable that systematically varies with the independent variable so that we cannot logically determine which variable is at work.

-if not controlled, then you cannot work to determine which variable is at work

reliability?

-consistency of measurement

-For example: Stepping on a scale

Validity?

The ability of a test to measure what it is intended to measure

Hypothesis testing?

-is the process of drawing conclusions about whether a particular relation between variables is supported by the evidence

-typically researchers examine data from a sample to draw conclusions about a population but there are many ways to conduct research

An Operational definition?

- specifies the operations or procedures used to measure or manipulate a variable

Correlation?

- is an association between two or more variables

- A correlation is one way to test a hypothesis, but it's not the only way, researchers prefer to conduct an experiment rather than a correlational study because it is easier to interpret the results of the experiment

when conducting experiments to control for confounding variables we??

what do researchers prefer?

- Random assignment: every participant in a study has an equal chance of being assigned to any of the groups, or experimental conditions, in the study.

- An experiment: is a study in which ppl are randomly assigned to a condition or level of one or more independent variables.

-When possible, researchers prefer to use an experiment rather than a correlational study, as experiments use random assignments, which is the only way to determine whether one variable causes another

what are the two different experimental designs?

- Between groups design: ppl experience one and only one level of the independent variable

-for example: random assignment

- Within groups research design: all ppl in the study experience different levels of the independent variable, also called repeated measure design. Anything that tests a before and after is a within groups design

- for example: sample taken from the population, randomly assign them to an order

Data ethics?

- is a set of principles related to all stages of working with the data research design, data collection, stats analysis and reporting outcomes

Open science?

- is an approach to research that encourages collaboration, and includes the sharing of research methodology. Data and stats analysis in ways that allow others to question and even try to recreate findings

a research team investigated the impact of texting during class on student performance, students listened to a lecture with either texting with a friend or not using their phones. they were randomly assigned to one of the two conditions and then quizzed on the lecture material after the lecture ended. scores on the quiz ranged from 0-100

what kind of design was this?

what was the dependent variable?

what was the independent variable?

- between groups design, because they were randomly selected

-The dependent variable: was the quiz performance

-independent variable: was the texting yes and no (2 levels)

a research team investigated how age influences attitudes towards the elderly, they had children, teens and young adults and older adults list as many positive things as they could about elderly people. The number of positive things listed was counted for each person.

what was the design?

what was the dependent variable?

what was the independent variable?

-within-group design, because it was a sample taken from a population

-the dependent variable: attitudes towards elderly ppl (# of positive things )

-independent variable: age groups, children, teens, young adults and older adults.

which are used in inferential statistics, samples or populations?

-They use sample data to draw conclusions of a larger population

If your professor calculated the average grade for the class, what would that be considered, the descriptive or inferential stat?

descriptive stat, because its only being used to describe the tendency of ppl in your class

If the same class average is used to predict something about how future students might do in statistics, would it be considered descriptive statistics or inferential statistics?

in this case, an inferential stat because it is being used to estimate the results of a population

Columbia university researcher Andrew, wrote about his research in NY 2013, The av american knows 600 people. How do we know this is true? Researchers led by columbian Tian posted a series of questions to a representative sample of 1500 Americans.

a) What is the sample?

b)What is the population?

c) what is the descriptive stat?

a) 1500 Americans

b) all Americans

c) 1500 Americans in the sample know 600 ppl on Average

What is the difference between continuous observations and discrete observations?

Discrete observations can take on only specific values, usually whole numbers, while continuous observations can take on a full range of values

Three students complete a Stroop task, Lorna finishes in 12.67s, Desiree finishes in 14.87s, and Marianne finishes in 9.88s.

a) are these data discrete or continuous?

b) is the variable an interval or a ratio observation?

c)on an ordinal scale, what is Lorna's score? On an ordinal scale, Lornas would be 2, or 2nd

a) This data is continuous because it take on a full range of values

b) The variable is a ratio observation because there is a true zero point

c) On an ordinal scale, Lornas would be 2, or 2nd

Dr. Nkembe is interested in examining whether employment status, which he codes by assigning 1 for employed and 2 for unemployed, predicts political affiliation, which he codes by assigning 1 for Democrat, 2 for Republican, 3 for other, and 4 for not affiliated. In this example, political party is a(n) _____ variable.

nominal

Dr. Phillips is interested in whether study techniques are related to major in college. To study this, she recruits 20 students from each major on campus to participate in her study and uses this information to draw conclusions about the population of interest. This exemplifies:

hypothesis testing

A study comparing the same group of participants before and after they receive a new treatment for depression is called a _____ research design.

Within groups design

A study comparing the same group of participants before and after they receive a new treatment for depression is an example of a(n) _____ that has a _____ research design.

experiment; within groups design

A psychology professor assigns her class to read a research article. The abstract for the article starts with the words, "In this experiment . . ."; it then goes on to provide a brief summary of the study. From this information, one can be sure that the:

participants were randomly assigned to conditions