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hypotheses."},{"text":"Inferential statistics.","correct":false,"explanation":"Inferential statistics use tests to determine significance and draw conclusions beyond a sample. Graphs visually summarise data, so the correct category is descriptive statistics."},{"text":"Parametric statistics.","correct":false,"explanation":"Parametric statistics are inferential tests based on assumptions about the data’s distribution. Graphs are methods of presenting data and therefore belong to descriptive statistics."},{"text":"Qualitative statistics.","correct":false,"explanation":"Qualitative data may be displayed graphically, but “qualitative statistics” is not the relevant category. Graphs summarise observed results, making them part of descriptive statistics."}]},{"id":"dcf09c39-b301-47ed-a7c7-1d94482cbb34","cardType":"basic","points":1,"front":"What can a graph not prove by itself?","back":"Statistical significance, e.g. $p \\le 0.05$.","mcqOptions":[{"text":"Statistical significance, e.g. $p \\le 0.05$.","correct":true,"explanation":"A graph can display an apparent pattern or difference, but only an appropriate inferential statistical test can establish whether the result is statistically significant."},{"text":"An apparent trend, e.g. scores increasing across conditions.","correct":false,"explanation":"A graph can visually display an apparent trend across conditions. What it cannot establish by itself is statistical significance, which requires an inferential test and a probability value."},{"text":"The highest frequency, e.g. the modal interval.","correct":false,"explanation":"The tallest bar can identify the interval with the highest frequency. However, a graph alone cannot demonstrate statistical significance, which must be assessed using an inferential test."},{"text":"A distribution’s shape, e.g. positive skew.","correct":false,"explanation":"The shape and skew of a distribution can be observed from a suitable graph. Statistical significance cannot be proved visually and requires an appropriate inferential test."}]},{"id":"5bd22173-faca-40df-b51f-04f575010969","cardType":"cloze","points":null,"front":"The original scores collected before organisation, summary or analysis are [ ].","back":"The original scores collected before organisation, summary or analysis are raw data.","mcqOptions":[{"text":"raw data","correct":true,"explanation":"Raw data are the original scores or observations exactly as collected, before researchers organise, summarise, code or statistically analyse them."},{"text":"grouped data","correct":false,"explanation":"Grouped data have already been organised into categories or class intervals. Original, unorganised scores collected directly by the researcher are called raw data."},{"text":"coded data","correct":false,"explanation":"Coded data have been converted into symbols or numerical categories for analysis. Before this processing occurs, the original collected scores are raw data."},{"text":"summary data","correct":false,"explanation":"Summary data present condensed information, such as averages or totals, rather than the original scores. Scores before any summarisation or analysis are raw data."}]},{"id":"0f47d569-1212-4238-a034-373c70b08624","cardType":"cloze","points":null,"front":"A score's frequency is how many times that score, category or interval [ ].","back":"A score's frequency is how many times that score, category or interval appears/occurs.","mcqOptions":[{"text":"appears/occurs","correct":true,"explanation":"Frequency records how often a particular score, category or interval appears or occurs within a data set."},{"text":"is ranked/ordered","correct":false,"explanation":"Ranking places scores in order but does not count how often they occur. Frequency is the number of times a score, category or interval appears or occurs."},{"text":"is totalled/summed","correct":false,"explanation":"Totalling combines numerical values rather than counting occurrences. Frequency states how many times a particular score, category or interval appears or occurs in the data."},{"text":"is estimated/predicted","correct":false,"explanation":"Estimating or predicting produces an expected value rather than an occurrence count. Frequency describes how many times a score, category or interval appears or occurs."}]},{"id":"9867b047-9ab5-4b56-8501-36b3e43efe96","cardType":"basic","points":2,"front":"Why add all frequencies after making a frequency table?","back":"To check the total matches participants/observations.","mcqOptions":[{"text":"To check the total matches participants/observations.","correct":true,"explanation":"Every participant or observation should contribute to the frequency total. Adding the frequencies therefore checks that no cases have been omitted or counted more than once."},{"text":"To check the total matches the mean score.","correct":false,"explanation":"The sum of frequencies gives the number of observations, not the mean. It should be checked against the number of participants or observations to identify counting errors."},{"text":"To check each frequency matches the median.","correct":false,"explanation":"The median is the middle score and does not need to equal any frequency. Frequencies are added to check that their total matches all participants or observations."},{"text":"To check the intervals match the range.","correct":false,"explanation":"The range concerns the difference between the highest and lowest scores, not the frequency total. Frequencies are summed to check they account for all participants or observations."}]},{"id":"ed1c59cc-d1a8-4571-a6d8-c820d0a95b4b","cardType":"basic","points":1,"front":"Which graph should show separate conditions, such as quiet room vs noisy room?","back":"Bar chart.","mcqOptions":[{"text":"Bar chart.","correct":true,"explanation":"A bar chart compares discrete categories or conditions, such as quiet and noisy rooms. Gaps between its bars show that the conditions are separate."},{"text":"Histogram.","correct":false,"explanation":"A histogram represents continuous scores grouped into intervals, with adjoining bars. Separate experimental conditions are categorical, so they should be displayed using a bar chart."},{"text":"Scattergram.","correct":false,"explanation":"A scattergram displays the relationship between two co-variables for paired scores. Separate conditions such as quiet and noisy rooms require a bar chart."},{"text":"Line graph.","correct":false,"explanation":"A line graph is most suitable when values form an ordered or continuous sequence. Distinct conditions are separate categories and are therefore better shown using a bar chart."}]},{"id":"37775169-fda9-42bf-a084-45477de2917d","cardType":"cloze","points":null,"front":"A bar chart uses [ ] between bars to show categories are separate.","back":"A bar chart uses gaps between bars to show categories are separate.","mcqOptions":[{"text":"gaps","correct":true,"explanation":"Gaps visually separate the bars because each bar represents a distinct category or condition rather than an adjoining interval on a continuous scale."},{"text":"lines","correct":false,"explanation":"Lines between bars do not indicate that categories are discrete. Bar charts use gaps to separate categories, whereas adjoining bars are characteristic of histograms."},{"text":"arrows","correct":false,"explanation":"Arrows are not the convention used to distinguish separate categories. Bar charts use gaps between bars to show that each category or condition is discrete."},{"text":"overlaps","correct":false,"explanation":"Overlapping bars would obscure category boundaries rather than show separation. Bar charts use gaps between bars to indicate that the categories are distinct."}]},{"id":"cbe2616a-a951-41b6-9867-efda4f2790e0","cardType":"basic","points":1,"front":"Which graph should show continuous scores grouped into intervals?","back":"Histogram.","mcqOptions":[{"text":"Histogram.","correct":true,"explanation":"A histogram displays continuous numerical data grouped into class intervals. Its bars touch because the intervals lie next to one another on a continuous scale."},{"text":"Bar chart.","correct":false,"explanation":"A bar chart displays separate categories or conditions and normally has gaps between bars. Continuous scores grouped into adjoining intervals should be shown using a histogram."},{"text":"Scattergram.","correct":false,"explanation":"A scattergram plots paired scores to investigate a correlation between two co-variables. A histogram is used to display the frequencies of grouped continuous scores."},{"text":"Line graph.","correct":false,"explanation":"A line graph connects values to show change across an ordered sequence, often time. Frequencies for continuous score intervals are conventionally displayed using a histogram."}]},{"id":"c765e27b-5c12-4269-9a09-f6c1572abcba","cardType":"cloze","points":null,"front":"Histogram bars [ ] because score intervals form a continuous scale.","back":"Histogram bars touch because score intervals form a continuous scale.","mcqOptions":[{"text":"touch","correct":true,"explanation":"Histogram intervals form a continuous numerical scale, so there are no gaps between adjacent categories. The bars therefore touch to represent continuity."},{"text":"overlap","correct":false,"explanation":"Overlapping bars would suggest that the same scores belong to multiple intervals. Histogram bars should touch, because adjacent intervals form a continuous scale without overlapping."},{"text":"separate","correct":false,"explanation":"Separating the bars is appropriate for discrete or categorical data. Histogram bars should touch because their score intervals lie next to one another on a continuous scale."},{"text":"alternate","correct":false,"explanation":"Alternating bars has no role in representing continuous data and would omit intervals. Histogram bars should touch because every adjacent score interval is part of the scale."}]},{"id":"07992e66-1403-4588-b282-647a5bb1542e","cardType":"cloze","points":null,"front":"Use a [ ] when movement across the x-axis matters, such as time or trial number.","back":"Use a line graph when movement across the x-axis matters, such as time or trial number.","mcqOptions":[{"text":"line graph","correct":true,"explanation":"A line graph connects successive measurements, making changes across an ordered x-axis, such as time, trials or conditions, easy to identify."},{"text":"pie chart","correct":false,"explanation":"A pie chart displays proportions of a whole rather than change across an ordered scale. A line graph shows movement across time or trial number."},{"text":"scatter diagram","correct":false,"explanation":"A scatter diagram examines the relationship between paired measurements, not movement through ordered stages. A line graph is appropriate when x-axis progression matters."},{"text":"histogram","correct":false,"explanation":"A histogram displays the frequency distribution of continuous scores. A line graph is needed to show how measurements change across time or successive trials."}]},{"id":"93aac708-c0f4-4321-b3b4-747eda1247cd","cardType":"basic","points":1,"front":"Which graph should show percentages of participants choosing each response option?","back":"Pie chart.","mcqOptions":[{"text":"Pie chart.","correct":true,"explanation":"A pie chart represents each response category as a proportion of the whole sample, so the slice sizes can directly show participant percentages."},{"text":"Histogram.","correct":false,"explanation":"A histogram represents frequencies across continuous score intervals, not separate response choices. A pie chart shows each response option as a percentage of the whole."},{"text":"Scatter diagram.","correct":false,"explanation":"A scatter diagram plots paired scores to examine a relationship between variables. A pie chart is appropriate for displaying percentages choosing categorical response options."},{"text":"Line graph.","correct":false,"explanation":"A line graph emphasises change across an ordered x-axis, such as time. A pie chart instead displays how the total percentage is divided among response options."}]},{"id":"7701bd9f-6890-43a3-a249-535ee9a7c506","cardType":"basic","points":1,"front":"What is the formula for a pie chart slice angle?","back":"Slice angle $= \\frac{\\text{category frequency}}{\\text{total frequency}} \\times 360$.","mcqOptions":[{"text":"Slice angle $= \\frac{\\text{category frequency}}{\\text{total frequency}} \\times 360$.","correct":true,"explanation":"Dividing the category frequency by the total gives its proportion of the data. Multiplying that proportion by 360 converts it into an angle for the circle."},{"text":"Slice angle $= \\frac{\\text{total frequency}}{\\text{category frequency}} \\times 360$.","correct":false,"explanation":"This reverses the fraction, producing angles that can exceed a full circle. Divide category frequency by total frequency, then multiply the resulting proportion by 360."},{"text":"Slice angle $= \\frac{\\text{category frequency}}{\\text{total frequency}} \\times 100$.","correct":false,"explanation":"Multiplying by 100 converts the proportion into a percentage, not an angle. A pie chart is a 360-degree circle, so the proportion must be multiplied by 360."},{"text":"Slice angle $= \\frac{\\text{category frequency}}{360} \\times \\text{total frequency}$.","correct":false,"explanation":"This treats 360 as a divisor and multiplies by the sample size, so it does not convert a proportion into degrees. Use category frequency divided by total frequency, multiplied by 360."}]},{"id":"15e70cd1-d9cf-4765-8d9e-c1ff5ace35ec","cardType":"basic","points":1,"front":"Which graph should show the relationship between two measured variables where neither is manipulated?","back":"Scatter diagram.","mcqOptions":[{"text":"Scatter diagram.","correct":true,"explanation":"A scatter diagram plots each participant’s paired measurements, allowing the direction and strength of the relationship between two co-variables to be examined."},{"text":"Pie chart.","correct":false,"explanation":"A pie chart shows how categories form proportions of a whole, rather than relationships between paired measurements. A scatter diagram is used for two measured variables."},{"text":"Histogram.","correct":false,"explanation":"A histogram displays the frequency distribution of one continuous variable. A scatter diagram plots paired scores to reveal a relationship between two measured variables."},{"text":"Line graph.","correct":false,"explanation":"A line graph usually shows change across an ordered x-axis. A scatter diagram is required when examining association between two variables without manipulating either one."}]},{"id":"c8abfe1c-4309-4a25-823d-b955ec43f2e3","cardType":"cloze","points":null,"front":"In a scatter diagram, each dot represents one participant's [ ].","back":"In a scatter diagram, each dot represents one participant's pair of scores.","mcqOptions":[{"text":"pair of scores","correct":true,"explanation":"Each dot is plotted using one score on the x-axis and the corresponding score on the y-axis, creating a pair for one participant."},{"text":"average score","correct":false,"explanation":"A dot does not usually represent a participant’s mean across measures. It represents that participant’s pair of scores, one for each measured variable."},{"text":"frequency total","correct":false,"explanation":"Frequencies are displayed in graphs such as histograms, rather than by individual scatter points. Each dot represents one participant’s pair of scores on the two variables."},{"text":"experimental condition","correct":false,"explanation":"Conditions are categories or levels of an independent variable, not paired coordinates. Each scatter point represents one participant’s pair of scores on two measured variables."}]},{"id":"6eedf046-3ccb-4333-92dd-5ce1a9e2cb95","cardType":"basic","points":1,"front":"What pattern shows a positive correlation on a scatter diagram?","back":"Both variables increase together.","mcqOptions":[{"text":"Both variables increase together.","correct":true,"explanation":"In a positive correlation, higher values of one variable are associated with higher values of the other, producing an overall upward trend in the points."},{"text":"One variable increases as the other decreases.","correct":false,"explanation":"This describes a negative correlation, because the variables move in opposite directions. A positive correlation occurs when both variables tend to increase together."},{"text":"There is no consistent relationship between variables.","correct":false,"explanation":"An absence of a consistent trend indicates zero or negligible correlation. A positive correlation has an upward pattern because both variables tend to increase together."},{"text":"The points form a curved relationship.","correct":false,"explanation":"A curved pattern indicates a non-linear relationship and does not by itself show positive correlation. Positive correlation requires an overall increase in both variables together."}]},{"id":"7fbbc0d3-eb54-4975-8715-69f069571702","cardType":"basic","points":1,"front":"What pattern shows a negative correlation on a scatter diagram?","back":"As one variable increases, the other decreases.","mcqOptions":[{"text":"As one variable increases, the other decreases.","correct":true,"explanation":"A negative correlation means higher values on one variable are associated with lower values on the other, creating an overall downward trend in the scatter points."},{"text":"As one variable increases, the other increases.","correct":false,"explanation":"Variables increasing together indicate a positive correlation, not a negative one. In a negative correlation, one variable decreases as the other increases."},{"text":"As one variable increases, the other stays constant.","correct":false,"explanation":"A constant second variable would not show the opposing movement required for negative correlation. In a negative correlation, the other variable tends to decrease."},{"text":"As one variable increases, the other changes randomly.","correct":false,"explanation":"Random changes indicate no consistent correlation rather than a negative one. Negative correlation produces a downward trend because the other variable tends to decrease."}]},{"id":"5b5061b8-1f3b-4d2e-b5c2-c33ad38f1345","cardType":"basic","points":1,"front":"What should you avoid claiming from a scatter diagram alone?","back":"Causation.","mcqOptions":[{"text":"Causation.","correct":true,"explanation":"A scatter diagram can show an association between two co-variables, but it cannot establish that changes in one variable directly cause changes in the other."},{"text":"Correlation.","correct":false,"explanation":"A scatter diagram can legitimately indicate correlation through the direction and closeness of plotted points. Causation must be avoided because correlation alone cannot demonstrate a cause-and-effect relationship."},{"text":"A relationship.","correct":false,"explanation":"The pattern of points can provide evidence of a relationship between two co-variables. The unjustified claim is causation, because other variables or chance may explain the association."},{"text":"A trend.","correct":false,"explanation":"An upward or downward trend can be identified from the plotted points. Causation cannot be inferred because a scatter diagram does not control extraneous variables or establish cause and effect."}]},{"id":"1b9e2253-24c7-4623-b141-9639406e625f","cardType":"cloze","points":null,"front":"A normal distribution is [ ]; the mean, median and mode are in the [ ].","back":"A normal distribution is symmetrical/bell-shaped; the mean, median and mode are in the same central position.","mcqOptions":[{"text":"A normal distribution is symmetrical/bell-shaped; the mean, median and mode are in the same central position.","correct":true,"explanation":"A normal distribution has equal-shaped halves around its centre. Because its scores are distributed symmetrically, the mean, median and mode all coincide at the central peak."},{"text":"A normal distribution is positively skewed; the mean, median and mode are in the same central position.","correct":false,"explanation":"Positive skew involves a long right-hand tail and separates the measures of central tendency. A normal distribution is symmetrical/bell-shaped, with all three measures in the same central position."},{"text":"A normal distribution is symmetrical/bell-shaped; the mean, median and mode are in three different positions.","correct":false,"explanation":"Three different positions are characteristic of a skewed distribution, where the mean is pulled towards the tail. In a normal distribution, all three occupy the same central position."},{"text":"A normal distribution is negatively skewed; the mean, median and mode are in three different positions.","correct":false,"explanation":"This describes a distribution with a long left-hand tail rather than a normal distribution. A normal distribution is symmetrical/bell-shaped, and its mean, median and mode share the same central position."}]},{"id":"f1b3173d-ac62-4bc9-be07-7990d9a4c231","cardType":"basic","points":1,"front":"A long tail to the right with a few unusually high scores indicates which distribution?","back":"Positive skew.","mcqOptions":[{"text":"Positive skew.","correct":true,"explanation":"A positively skewed distribution has a long tail extending towards the higher scores on the right. A small number of unusually high values pull the mean in that direction."},{"text":"Negative skew.","correct":false,"explanation":"Negative skew has a long tail towards unusually low scores on the left, not high scores on the right. A right-hand tail indicates positive skew."},{"text":"Normal distribution.","correct":false,"explanation":"A normal distribution is approximately symmetrical, so it does not have a pronounced tail on only one side. A long right-hand tail indicates positive skew."},{"text":"Bimodal distribution.","correct":false,"explanation":"A bimodal distribution is identified by two distinct peaks, not by the direction of a long tail. Unusually high scores creating a right-hand tail indicate positive skew."}]},{"id":"a7000d35-f873-4f93-a46a-3676b144bba1","cardType":"basic","points":1,"front":"In a positive skew, what is the typical order of mode, median and mean?","back":"Mode → median → mean.","mcqOptions":[{"text":"Mode → median → mean.","correct":true,"explanation":"In a positive skew, the mode remains near the peak, the median lies farther right, and unusually high scores pull the mean furthest towards the right-hand tail."},{"text":"Mean → median → mode.","correct":false,"explanation":"This reverses the effect of the right-hand tail and is the typical left-to-right order for negative skew. In positive skew, the order is mode, median, then mean."},{"text":"Median → mode → mean.","correct":false,"explanation":"The mode is normally closest to the peak and therefore lies left of the median in positive skew. The correct order is mode, median, then mean."},{"text":"Mode → mean → median.","correct":false,"explanation":"This underestimates how strongly extreme high scores affect the mean. The mean is pulled furthest towards the right-hand tail, giving the order mode, median, then mean."}]},{"id":"c7b99e8c-7854-4d81-ad12-5a784e08ad4a","cardType":"basic","points":1,"front":"A long tail to the left with a few unusually low scores indicates which distribution?","back":"Negative skew.","mcqOptions":[{"text":"Negative skew.","correct":true,"explanation":"A negatively skewed distribution has a long tail extending towards the lower scores on the left. A small number of unusually low values pull the mean in that direction."},{"text":"Positive skew.","correct":false,"explanation":"Positive skew has a long tail towards unusually high scores on the right, not low scores on the left. A left-hand tail indicates negative skew."},{"text":"Normal distribution.","correct":false,"explanation":"A normal distribution is approximately symmetrical and therefore lacks a pronounced one-sided tail. A long tail created by unusually low scores indicates negative skew."},{"text":"Bimodal distribution.","correct":false,"explanation":"A bimodal distribution contains two distinct peaks, whereas skew concerns an extended tail on one side. A tail towards unusually low scores indicates negative skew."}]},{"id":"1b9b93a1-6758-40b9-b23c-13fced440671","cardType":"basic","points":1,"front":"In a negative skew, what is the typical order of mean, median and mode?","back":"Mean → median → mode.","mcqOptions":[{"text":"Mean → median → mode.","correct":true,"explanation":"In a negative skew, unusually low scores pull the mean furthest towards the left-hand tail. The median lies between the mean and the mode, which remains near the peak."},{"text":"Mode → median → mean.","correct":false,"explanation":"This is the typical left-to-right order for a positive skew, where high scores pull the mean rightwards. In negative skew, the order is mean, median, then mode."},{"text":"Median → mean → mode.","correct":false,"explanation":"The left-hand tail pulls the mean farther left than the median, so the median cannot come first. The correct order is mean, median, then mode."},{"text":"Mean → mode → median.","correct":false,"explanation":"Although the mean is correctly placed nearest the left-hand tail, the median and mode have been reversed. The mode remains near the peak, giving mean, median, then mode."}]}]}],"examCountdown":{"examDate":"2027-05-18","paperLabel":"Component 1"},"heading":"Graphical representation","title":"Graphical representation Flashcards","topbar":{"backHref":"/a-level/psychology/eduqas/flashcards"},"topicSidebar":"$L38"}]}],"topicId":"c2122c92-3660-52a6-8fa6-084b047dc139","walled":"$L39"}],"$L3a","$L3b"]