# Data Analysis with R

Problem 1

Use aggregate, tapply, or similar to determine the mean and sds for the following, and answer these questions. For each, show tables, and write text that both asks and answers the following questions. When you observe a difference, explain why you might have seen this and what it might mean.

(a) What was the effect of time of day on RT and accuracy?

(b) What was the effect of session on RT and accuracy?

(c) What was the effect of the correct response side (i.e., order) on RT and accuracy?

(d) Was there improvement in RT/accuracy within trial blocks? Answer this both overall, and for only block 1.

(e) Categorize the sessions into three session blocks: 1-4, 5-8, and 9-12. What was the effect of time of day and session block (i.e., a 4x3 table) on RT and accuracy?

Problem 2

For each part of 1, create a figure that shows the effect on response time. Across the different parts, use each of the following at least once: a barchart with error bars specifying either standard deviation or standard error, a matrix plot (matplot), a boxplot, and a plot where you overlay means on top of individual data points (similar to a bandplot). Each plot must use colors. For each plot, full credit will only be given for figures that are fully annotated and labeled. Write a figure caption for each, as it would appear in a paper in which you used each plot, indicating what is being shown (e.g., what are the error bars, the dv, etc.).

Problem 3 .

Create a function that takes as its argument a session id and participant code, as well as the data, like this:

PlotCombo <- function(subnum,session,data) {...}

PlotCombo should:

(a) use the entire data set as an input for the data argument

(b) select the subset of data that match the given values of subnum and session.

(c) If an illegal combination is given (i.e, one such that the resulting data set is empty), it should exit with a warning, but create an empty plot that reads something like ”no data available”. Be sure to demonstrate and test that this works.

(d) Create a plot of mean response time by trial number for that session:

(e) Make titles or text that label the session, and subject code for the data set, as well as the time-of-day (tod).

Once the PlotCombo is complete, using either the pdf() command or an RMarkdown file, create a multipage summary that shows each participant by iterating over at least the first 8 blocks of each participant, (e.g., plotting a 2x4 or 4x2 grid on each page.) If you call pdf(), it will automatically create new pages once each page is filled, and save the file when [login to view URL]() is called. For example, something like:

PlotCombo(3,1,data)

PlotCombo(3,2,data)

PlotCombo(3,3,data)

Again, be sure describe what you have found–are there any patterns, outliers, or interesting results? 2

Some pointers

1. Be sure you do a good job at describing the results, labeling figures, interpreting what is going on and using the data to back it up. Show and Tell

2. Don’t just turn in a dump of output. Treat this as a deliverable for a customer, or a prospective customer, or a boss. Think about things like significant digits, cleanliness of figures, use of irrelevant colors, etc. axis labels, and using common color themes. Don’t use of default labels unless they are appropriate. Choose appropriate x and y limits, and make sure your figures are readable in the document you turn in..

Budget is \$30 bid only if you can work within budget

Keahlian: Data Analytics, Bahasa Pemrograman R

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mlaha

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