KS3 Level

Data

Projected KS4 Grades

6

I can construct on paper scatter graphs, identify the types of correlation by drawing lines of best fit. I can justify the suitability of a given bar chart, pie chart, line graph, scatter graph with reference to the context of the problem and the audience. I can interpret a Stem and Leaf Diagram in order to calculate the averages and range. I can estimate the mean from a grouped frequency table. I can calculate and find the range, modal class and interval containing the median of a grouped data frequency table. I can recognise the advantages and disadvantages between measures of average  mixed in with previous objectives

I can write the questions and response sections for a questionnaire. I understand the difference between a sample and a full population and the justification for a sample and a sample size I understand and can plan to minimise bias using a random sample selection. I can construct a frequency table with equal class intervals for discrete data making sure there are no overlaps in the data. I can collect data using a predrawn tally/frequency table for continuous data, discussing what the inequalities mean. I can construct on paper, line graphs for time series. Understand and identify key features present in the data of this type of graph.

9

5

I can interpret a variety of different graphs, taking into account different sized samples comparing two or more data sets. I can identify when the events in a problem are mutually exclusive and apply the knowledge that the sum of probabilities of all mutually exclusive outcomes is 1. I can explain why that if the probability of an event occurring is p, then the probability of it not occurring is (1−p) and use the fact that the probability of an event occurring is p, then the probability of it not occurring is (1 − p) to calculate probabilities. I can draw frequency trees based on given information to show expected outcomes. I can use a frequency tree to find a probability.

I can use tables or lists to calculate a missing probability by constructing algebraic equations. I understand and can use very simple set notation to describe parts of the Venn diagram (e.g P(A)) I can compare experimental probabilities with theoretical probabilities recognising that if an experiment is repeated the outcome may, and usually will be different and that that increasing the number of times an experiment is repeated generally leads to better estimates of probability.

8

4

I can decide on the type of data appropriate for data collection. I can write a hypothesis to investigate a given situation, giving reasoning as to whether it may be true or false. I can identify where the different methods of data collection might be used and why a given method may or not be suitable in a given situation. I understand how and why bias may arise in the collection of data and I can offer ways of minimising bias for a data collection method.

I can construct a frequency table for discrete data including quantitative and qualitative data. You understand the reasoning between using grouped and ungrouped data and the advantages and drawbacks of grouping data in particular ranges. I can construct frequency diagrams and frequency polygons for continuous data. You understand and can identify key features present in the data of this type of graph.

7

3

I can draw and produce stem and leaf diagrams. I can construct pie charts for a given set of data. You understand and can identify key features present in the data of this type of graph. I can calculate the mean from a frequency table. I can compare two simple distributions using the range and the mean

I understand the differences between the three averages and can determine which one is appropriate to use with discrete data. I can interpret pie charts taking into account different sized samples and using simple fractions, percentages and multiples of 10% sections. I can compare two distributions displayed in pie charts.

6

2

You can find and justify probabilities for outcomes of an event, based on equally likely outcomes. You can calculate the theoretical probability of an outcome. You can determine probabilities from frequency tables and twoway tables. You can use Venn diagrams to record all outcomes for single events and derive related probabilities.

You can calculate experimental probabilities by collecting data from a simple experiment and recording it in a table. You can estimate the number of times an outcome will occur, given the theoretical probability and the number of trials.

5

1

I can decide on the type of data appropriate for data collection I understand the reasoning between using grouped and ungrouped data, and understand the advantages and disadvantages of grouping data in particular ranges

I can draw stem and leaf diagrams I can construct bar charts for discrete data, include grouped data. I can understand and identify key features present in the data of bar charts then extend to constructing a comparative/dual bar chart for discrete data

4

WT+

I can describe the likelihood of familiar events using the language of probability (e.g. even, unlikely, etc.). I can use the key probability words and know how these apply to the probability scale from 0 to 1. I can use probability vocabulary when interpreting results from and experiment • I can write probabilities in words, fractions, decimals and percentages I can identify all of the mutually exclusive outcomes of a single event and list them in a systematic way. I can then extend to exploring and recording outcomes for two or more successive events in a systematic way eg. a two way table or a frequency table

I can compare differing sets of data using the range, median and mode I can find the median group and modal class from a grouped frequency table for continuous data • I can calculate the mean from a set of discrete data • I can explain the results from a bar chart by working out possible frequencies. I can identify that the mode is represented by the largest section/tallest bar. I can interpret and/or compare bar graphs and frequency diagrams which are misleading (with false origins, different scales etc.) I can compare two or more data sets and make inferences based on the shape of the bar chart including measures of average and spread I understand the difference between experimental and theoretical probability. You understand the terms ‘fair’ and ‘bias’ in regards to experimental probabilities (e.g. use an experiment to see if a dice is biased)

3

WT

2

WT

1
