    Mathematics High School Assessment Field Tests: What We Are Learning from the Algebra/Data Analysis HSA? Areas of Growth: Students are responding more to the constructed response items and the quality of their responses is improving.  Students' responses addressing the cue for an explanation are more clearly presented and fully developed.  Students' understanding of Goal 3 content is improving. Informing Instruction: Students will continue to benefit from: Justifying their answers. An appropriate justification may include:  a statement of a mathematical principle and/or a definition a demonstration that the solution satisfies the conditions of the problem  Writing equations to model a situation or to represent a pattern  Using a table of a linear function to find the y–intercept of the equation  Justifying that a pattern is a function  Finding the domain and range of functions from a graph  Recognizing the scales of the x– and y–axes are important, specifically:  the scales of the axes may be different the unit of the scales will not always be one  Using two points from a graph to determine the slope of a line  Interpreting the slope and y–intercept of lines in the context of the problem  Interpreting the solution of a system of equations in the context of the problem  Graphing inequalities for which the coefficient of the variable is negative   Interpreting frequency tables to find measures of central tendency  Understanding how measures of central tendency are effected by:  extreme data points changes in the data set  Reading and understanding box–and–whisker plots, including:  using measures of variability to interpret data and compare data sets recognizing that the mean cannot be determined from a box and whisker plot  Interpreting frequency tables to find probabilities from the results of a simulation or a survey  Understanding probability simulations, including:  distinguishing between a simulation and an experiment justifying that a simulation model represents a given probability defining a trial describing how to interpret the data from a simulation to calculate the experimental probability reading random number tables  Understanding sampling, including:  distinguishing between a representative and simple random sample designing a simple random sample recognizing how a simple random sample insures independent selection of the members of the sample as well as each member of the population having an equally likely chance to be chosen for the sample 