Kian has worked his way through the first two units of the textbook and has accumulated a broad-based knowledge of bivariate data. He confidently answers questions regarding type of data, explanatory vs response language inside a posed question, how to set up a scatterplot, apply a line of best fit, discuss values both inside/outside the data set, and talk about the reliability of the predictions made utilizing the line of best fit.

Kian should work all assigned homework problems on the day the work is assigned so the methodology remains top of mind for him. He has a strong overview of the first two units. His teacher will give him greater guidance on how to verbally describe differences/similarities in the data.

Coen excelled at the "butterfly method" of adding/subtracting fractions as the mechanics were "easy" and the thought process made sense to him. Once Coen realized that when multiplying and dividing fraction required him to change mixed numbers into improper fractions, he was able to do the math without problem. Coen prefers to multiply across rather than reducing before multiplying. Occasionally, he came up with large numbers that would have been manageable had he cross-reduced. Coen is becoming more comfortable with his classpad and did not have any difficulty inputting numbers/operations to double-check his work with fractions. Dividing an amount into a ratio using the unitary method made sense to him after seeing it again. He was able to correctly apply the mechanics to all the problems we worked together.

Coen occasionally confuses price per unit for unit per price, which is totally backward. I suggested that when he's comparing two quantities of the same unit measure, that unit measure should be in the denominator. Changing revolutions to minutes when given minutes in fraction form caused him difficulty. He should continue to work these types of problems.

Maya quickly grasped the terminology and verbally answered all questions confidently. She was able to see how a percentage table, row and/or column, would be beneficial when comparing data sets. Additionally, once in the "stacked 100% column" form, she easily saw if an association was present and worked to read the data and discuss it. She identified positive, negative, and no correlation without issue, worked on the line of best fit, discussed interpolation versus extrapolation and the validity of the data, and looked at r, the correlation coefficient, to speak about the strength of the correlation. Maya learned to hedge her answer by using words such as "it appears," "tends to show," "may relate," in her constructed responses. Additionally, Maya noted that totals not adding to exactly 100% were caused by rounding.

Maya should read over the first two units again before the start of the school year.

Kian picks up new concepts quickly. He has an innate ability to cull through information quickly and accurately to find the relevant material and how to use it. His questions are insightful and he usually can project forward to how this new-found information can be used. He was exceptionally quick when it can to identifying the explanatory vs response variable. Additionally, he understood that in "time series data" time would always be the explanatory variable and plotted on the horizontal axis of the data plot. Kian was very curious about the correlation coefficient, which is between negative one and positive one, as it pertained to a data set. He quickly figured out that the closer the coefficient was to either to negative one or positive one, the stronger the correlation (more accurate the line of best fit)

Kian will be in Adelaide at a swim meet over the upcoming weekend so no homework was given. We will resume our discussion of bivariate data next week when he returns and will practice using the classpad to calculate items needed for this unit of study.