please before choosing a topic, send it to more to confirm it with the professor. dont start until i confirm the professor asked us to

please before choosing a topic, send it to more to confirm it with the professor. dont start until i confirm the professor asked us to

#Visualizations

Interpret, analyze, and create data visualizations.

Typically, one can understand data best by looking at it from multiple different perspectives, which can be facilitated by data visualization techniques—this is because the human brain did not evolve to be able rapidly to scan and make sense of columns of data. Histograms, cumulative histograms, difference histograms, bar graphs, line graphs, scatter plots, and many other types of graphics can provide insights into how to ask and answer questions. Different data visualization techniques have different strengths and weaknesses, and one must consider properties of the data and the questions of interest when deciding how best to use these tools.

Example

Your marketing firm is working with a company that is trying to increase product sales from existing customers. You have access to a range of data and create a few graphs to highlight potential areas of opportunity. You wonder if there are seasonal trends, so you construct a line graph of monthly sales, which show that sales substantially dip during winter months. A line graph is appropriate because of the temporal relationship the time series data have. Next, you wonder if particular demographic groups drive sales, so you create a bar graph to compare those groups. A bar graph is appropriate because the demographic groups membership is a categorical variable. Last, you wonder if income levels may relate to product sales, so you construct a scatter plot with income levels on the x axis and product sales per customer on the y axis. A scatter plot is appropriate because the two variables are continuous variables and you want to evaluate the relationship between them. For each graph, you ensure that you have proper axis labels with units, and a brief but informative caption. The insights the data visualizations provide help guide the marketing strategy.

Rubric

0

Did not submit the assigned item, or submitted something that does not meet the minimum standard.

1

Does not critique or apply tools for generating data visualizations when prompted, or does so entirely or mostly ineffectively; does not analyze or interpret data visualizations when prompted, or does so mostly or entirely inaccurately.

2

Critiques a data visualization only somewhat accurately; generates a somewhat effective data visualization; analyzes or interprets a data visualization only somewhat accurately.

3

Effectively generates a data visualization; effectively analyzes or interprets a data visualization; (when applicable) effectively critiques a data visualization.

4

Effectively generates a detailed data visualization appropriate for the data; effectively analyzes or interprets a data visualization and provide appropriate justification and details; (when applicable) effectively critiques a data visualization and clearly explains why certain methods are better for distinct data sets.

#HypothesisDevelopment

Evaluate the link between hypothesis-driven research and the theories or observations that motivate it.

Scientific research begins with observations, which then must be organized to suggest underlying patterns of regularity. Such patterns in turn suggest hypotheses about the nature of the factors that may give rise to these patterns in the data. As science progresses, scientists formulate and use theories to develop further hypotheses and design additional studies. A well-formed hypothesis requires one to appreciate the links between data, theories, and models. Hypothesis-driven research is essential to the iterative cycles of data collection and theorizing that forms the core of the scientific method.

Example

You read a story about Blue Moon butterflies in the Samoan Islands. The butterflies were attacked by a parasite that destroyed only male embryos and resulted in males being only 1% of the population. But after 10 generations (about 1 year) males are now 40% of the population. Based on these facts, you come up with two competing explanations: (a) an extinction event could have led to the sudden disappearance of the parasite, which would explain the sudden resurgence of male butterflies, or (b) male butterflies developed a resistance against the parasites, which might also explain such resurgence. Hypothesis (b) also stems from your knowledge of genetics and the plausibility of developing resistance to particularly harmful species through genetic mutations coupled with natural selective pressures. You discuss predictions that stem from these two explanations, specifically that in case (a) most parasites would be gone, and in case (b) that the parasites might still be present in butterflies that developed resistances. Finally, you make the connection between study design, testing the mentioned predictions, and deciding which of your hypothesis is corroborated. (And in fact, researchers found that the parasite was still present and that currently, males all carried the mutation that allowed them to survive the parasite’s attack.).

Rubric

0

Did not submit the assigned item, or submitted something that does not meet the minimum standard.

1

Does not identify a link between patterns in initial data and the generation of hypotheses when prompted, or does so mostly or entirely inaccurately; does not generate a hypothesis from data when prompted; does not recall or describe the theoretical basis for a study when prompted, or does so mostly or entirely inaccurately.

2

Identifies a link between patterns in initial data and the generation of hypotheses only somewhat accurately; generates a hypothesis from data only somewhat effectively; recalls or identifies the theoretical basis for a study only somewhat accurately or effectively.

3

Accurately identifies a link between patterns in initial data and the generation of testable hypotheses; (when applicable) generates a hypothesis from data effectively; (when applicable) accurately recalls or identifies the theoretical basis for a study.

4

Accurately identifies a link between patterns and initial data and the generation of hypotheses and clearly explains the connection; (when applicable) generates a hypothesis from data and provides a clear, well-supported justification; (when applicable) provides a clear explanation for how theories are linked to study design.

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